Jamie Heywood: The big idea my brother inspired

45,802 views ・ 2010-02-02

TED


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譯者: Coco Shen 審譯者: Geoff Chen
00:15
When my brother called me in December of 1998,
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我弟在98年12月打電話給我
00:18
he said, "The news does not look good."
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他說﹐我有一個壞消息
00:20
This is him on the screen.
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這就是他
00:22
He'd just been diagnosed with ALS,
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他剛知道他得了肌肉萎縮性側索硬化症
00:24
which is a disease that the average lifespan is three years.
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病患預期壽命是三年
00:28
It paralyzes you. It starts by killing
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這疾病會讓你完全失去行為能力
00:30
the motor neurons in your spinal cord.
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從殺死中樞神經中的運動神經元開始
00:33
And you go from being a healthy,
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你逐漸地從一個健康
00:35
robust 29-year-old male
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強壯的29歲男性
00:38
to someone that cannot breathe,
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變成一個無法呼吸
00:40
cannot move, cannot speak.
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無法移動﹐言語的人
00:46
This has actually been, to me, a gift,
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我把這次經驗看作一項禮物
00:50
because we began a journey
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我們開始學習
00:53
to learn a new way of thinking about life.
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用新的方法思考人生
00:56
And even though Steven passed away three years ago
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雖然 Steven 離開我們三年了
01:00
we had an amazing journey as a family.
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我們一起走過了一段神奇的旅途
01:02
We did not even --
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我們甚至沒有
01:05
I think adversity is not even the right word.
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我甚至不覺得這是不幸的事件
01:07
We looked at this and we said, "We're going to do something with this
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我們接受它﹐然後把它當成一次機會
01:10
in an incredibly positive way."
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用樂觀的態度面對
01:12
And I want to talk today
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我今天想對你們說的
01:14
about one of the things that we decided to do,
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便是我們決定要做的事情之一
01:17
which was to think about a new way of approaching healthcare.
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用一種嶄新的方式去思考醫療產業
01:21
Because, as we all know here today,
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在座的我們都知道
01:23
it doesn't work very well.
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現在的狀況並不是很理想
01:25
I want to talk about it in the context of a story.
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我希望用故事的方式和你們討論
01:28
This is the story of my brother.
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我弟弟的故事
01:30
But it's just a story. And I want to go beyond the story,
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我希望在他的故事以後
01:33
and go to something more.
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我們能發現我們能做的事還有很多
01:35
"Given my status, what is the best outcome
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“就我的疾病來說﹐什麼是最樂觀的情況
01:38
I can hope to achieve, and how do I get there?"
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我該怎麼做﹐才能達到那樣的情況﹖”
01:41
is what we are here to do in medicine, is what everyone should do.
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這便是醫療所該做的﹐每個人所該做的
01:44
And those questions all have variables to them.
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每個人的問題和解答都不同
01:46
All of our statuses are different.
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因為每個人的狀況不同
01:48
All of our hopes and dreams, what we want to accomplish,
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我們想達到的希望和夢想
01:50
is different, and our paths will be different,
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都有所不同﹐我們的路徑也不同
01:52
they are all stories.
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這些都是故事
01:54
But it's a story until we convert it to data
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但除非我們把這些故事變成數據
01:56
and so what we do, this concept we had,
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我們的概念是
01:58
was to take Steven's status, "What is my status?"
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把 Steve 的病情 “我的病情是什麼﹖”
02:01
and go from this concept of walking, breathing,
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把這個概念延伸到走路﹐呼吸
02:06
and then his hands, speak,
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手的移動﹐說話
02:09
and ultimately happiness and function.
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以及心理的情緒和各種反應
02:13
So, the first set of pathologies, they end up in the stick man
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第一組病狀﹐他們會組成圖片上的
02:15
on his icon,
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這個人形
02:17
but the rest of them are really what's important here.
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但其他的資料才是重要的
02:20
Because Steven, despite the fact that he was paralyzed,
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因為就算 Steven 已經癱瘓
02:23
as he was in that pool, he could not walk,
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他在泳池裡﹐他不能走動
02:26
he could not use his arms -- that's why he had the little floaty things on them,
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他不能移動手臂﹐所以才需要手臂上這些東西幫助他漂浮
02:28
did you see those? --
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看到了嗎﹖
02:30
he was happy. We were at the beach,
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他很快樂﹐我們在沙灘上
02:32
he was raising his son, and he was productive.
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他正舉起他的兒子﹐他還有反應
02:34
And we took this, and we converted it into data.
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我們把這些資料都變成數據
02:39
But it's not a data point at that one moment in time.
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這個數據不只是一個時間
02:41
It is a data point of Steven in a context.
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而是過程裡的一個時間點
02:43
Here he is in the pool. But here he is healthy,
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這時他在游泳池裡﹐但這裡他還很健康
02:45
as a builder: taller, stronger,
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一個又高又壯的建築工人
02:48
got all the women, amazing guy.
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所有的女孩都喜歡他﹐了不起的男人
02:50
Here he is walking down the aisle,
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然後他結婚
02:52
but he can barely walk now, so it's impaired.
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但他不太能走﹐有些顛簸
02:55
And he could still hold his wife's hand, but he couldn't do buttons on his clothes,
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他還可以牽著他太太的手﹐但他無法自己扣上釦子
02:57
can't feed himself.
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不能自己吃飯
02:59
And here he is, paralyzed completely,
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到最後﹐他完全癱瘓了
03:01
unable to breathe and move, over this time journey.
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他不能呼吸﹐不能動
03:03
These stories of his life, converted to data.
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他人生旅程化為數據
03:06
He renovated my carriage house
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他整修了我的馬廄
03:08
when he was completely paralyzed, and unable to speak,
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當他完全癱瘓﹐不能說話
03:10
and unable to breathe, and he won an award for a historic restoration.
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不能呼吸時﹐他贏得了歷史文物整修獎
03:16
So, here's Steven alone, sharing this story in the world.
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這是他一個人的故事
03:18
And this is the insight, the thing that we are
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這就是這件事的意義﹐也是
03:21
excited about,
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我們興奮之處
03:23
because we have gone away from the community that we are,
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我們從社區走出來
03:26
the fact that we really do love each other and want to care for each other.
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把我們對彼此的愛和關懷
03:29
We need to give to others to be successful.
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把它分享給他人
03:31
So, Steven is sharing this story,
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Steven 分享了他的故事
03:34
but he is not alone.
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但他並不孤單
03:36
There are so many other people sharing their stories.
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有許多其他人正分享他們的故事
03:38
Not stories in words, but stories in data and words.
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不只是語言﹐這些故事也由數據寫成
03:41
And we convert that information into this structure,
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我們把這些資料放進這個程式
03:44
this understanding, this ability to convert
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把這些理解從故事
03:47
those stories into something that is computable,
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化為可計算的數據
03:49
to which we can begin to change the way
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從這裡開始﹐我們可以改變
03:51
medicine is done and delivered.
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我們現有的健康醫療
03:53
We did this for ALS. We can do this for depression,
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從肌肉萎縮性側索硬化症﹐憂鬱症
03:55
Parkinson's disease, HIV.
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帕金斯症﹐愛滋病都可以用一樣的方法
03:57
These are not simple, they are not internet scalable;
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這並不容易﹐不只是用戶的增加
03:59
they require thought and processes
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還有更多考量和過程
04:01
to find the meaningful information about the disease.
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才能把這些疾病資料變成有意義的資訊
04:04
So, this is what it looks like when you go to the website.
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這是你進入網站時的畫面
04:07
And I'm going to show you what Patients Like Me,
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這個網站叫“病患如我”
04:10
the company that myself, my youngest brother
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是由我﹐我小弟
04:12
and a good friend from MIT started.
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和一個麻省理工的朋友一起創立的
04:14
Here are the actual patients, there are 45,000 of them now,
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現在有大約四萬五千個病患
04:17
sharing their stories as data.
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和我們分享他們的故事和數據
04:19
Here is an M.S. patient.
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這裡有個多發性硬化症病患
04:21
His name is Mike, and he is uniformly impaired
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他叫麥克﹐他的認知﹐視覺
04:23
on cognition, vision, walking, sensation.
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行走﹐感知都受損了
04:26
Those are things that are different for each M.S. patient.
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每個多發性硬化症病患都不太一樣
04:28
Each of them can have a different characteristic.
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每個人的病徵都不同
04:30
You can see fibromyalgia, HIV, ALS, depression.
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你可以看到纖維肌症﹐愛滋﹐憂鬱症﹐和肌肉萎縮性側索硬化症
04:35
Look at this HIV patient down here, Zinny.
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這裡有個叫金尼的愛滋病患
04:38
It's two years of this disease. All of the symptoms are not there.
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他已經得愛滋兩年了﹐還沒有出現任何病徵
04:41
But he is working to keep his CD4 count high
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他正努力保持高免疫細胞
04:43
and his viral level low so he can make his life better.
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和病毒數量低﹐讓他能夠過得更好
04:46
But you can aggregate this and you can discover things about treatments.
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綜合這些數據﹐就能發現不同治療所造成的差別
04:50
Look at this, 2,000 people almost, on Copaxone.
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這裡有兩千多個正在使用格拉默的病患
04:52
These are patients currently on drugs,
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這些正在用藥的病人一起
04:54
sharing data.
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分享數據
04:56
I love some of these, physical exercise, prayer.
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有些很棒﹐運動﹐禱告
04:59
Anyone want to run a comparative effectiveness study
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有人想要做禱告和其他治療法的比較研究嗎﹖
05:01
on prayer against something? Let's look at prayer.
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讓我們看看禱告
05:03
What I love about this, just sort of interesting design problems.
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我最喜歡的是這些有趣的設計問題
05:07
These are why people pray.
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這是人們禱告的原因
05:09
Here is the schedule of how frequently they -- it's a dose.
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這是他們禱告的頻率﹐像個劑量
05:11
So, anyone want to see the 32 patients that pray for 60 minutes a day,
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如果你想知道32個每天禱告60分鐘的病患是不是比較健康
05:14
and see if they're doing better, they probably are.
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療癒程度是不是比較好﹐答案是“是的”
05:16
Here they are. It's an open network,
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你可以看到﹐這些都是開放的
05:19
everybody is sharing. We can see it all.
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我們可以看到每個人分享的資訊
05:22
Or, I want to look at anxiety, because people are praying for anxiety.
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如果我想看焦慮症﹐人們為了焦慮而禱告
05:25
And here is data on 15,000 people's current anxiety, right now.
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這裡有一萬五千個焦慮患者的數據
05:30
How they treat it,
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他們如何治療
05:33
the drugs, the components of it,
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他們用的藥物﹐裡面的成份
05:36
their side effects, all of it in a rich environment,
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副作用﹐這裡有豐富的資料
05:39
and you can drill down and see the individuals.
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你可以繼續深入研究各個病患
05:41
This amazing data allows us to drill down and see
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這些驚人的數據讓我們深入了解
05:44
what this drug is for --
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這些藥物的作用
05:47
1,500 people on this drug, I think. Yes.
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一千五百個病患正在使用這個藥
05:49
I want to talk to the 58 patients down here
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讓我看看這58個病患
05:51
who are taking four milligrams a day.
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他們每天吃四毫克
05:53
And I want to talk to the ones of those that have been doing
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我想和他們對話﹐看看他們用了兩年以後
05:55
it for more than two years.
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現在的狀況如何
06:01
So, you can see the duration.
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你可以看見他們的療程
06:03
All open, all available.
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一切資料都是開放的
06:07
I'm going to log in.
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我現在要登錄
06:11
And this is my brother's profile.
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這是我弟弟的檔案
06:13
And this is a new version of our platform we're launching right now.
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這是我們最近開放的新版平臺
06:17
This is the second generation. It's going to be in Flash.
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第二代﹐用 Flash 播放器
06:19
And you can see here, as this animates over,
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你可以看到﹐當它移動的時候
06:22
Steven's actual data against the background of all other patients,
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Steven 的數據和其他病患的數據
06:25
against this information.
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相互比較
06:28
The blue band is the 50th percentile. Steven is the 75th percentile,
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藍色帶是五十個百分點﹐Steven 是七十五
06:30
that he has non-genetic ALS.
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他患的是非遺傳性的肌肉萎縮性側索硬化症
06:33
You scroll down in this profile and you can see
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這個檔案下面
06:35
all of his prescription drugs,
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有他所有處方藥的記錄
06:37
but more than that, in the new version, I can look at this interactively.
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不只這樣﹐新版本裡可以互動
06:40
Wait, poor spinal capacity.
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受損的脊椎功能
06:42
Doesn't this remind you of a great stock program?
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這是否令你想起那些很好的股票軟體﹖
06:44
Wouldn't it be great if the technology we used to take care of ourselves
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如果我們能把這些拿來賺錢的科技拿來照顧健康
06:46
was as good as the technology we use to make money?
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那不是很好嗎﹖
06:49
Detrol. In the side effects for his drug,
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托特羅定﹐這裡有藥物的副作用
06:51
integrated into that, the stem cell transplant that he had,
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結合幹細胞移植
06:53
the first in the world, shared openly for anyone who wants to see it.
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全世界第一個公開的資料站
06:59
I love here -- the cyberkinetics implant,
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我喜歡這個﹐植入性芯片
07:01
which was, again, the only patient's data that was online and available.
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這也是網路上唯一公開的病患數據
07:05
You can adjust the time scale. You can adjust the symptoms.
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你可以調整時間軸﹐症狀
07:07
You can look at the interaction between how I treat my ALS.
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我如何醫治我的肌肉萎縮性側索硬化症
07:11
So, you click down on the ALS tab there.
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點下面的肌肉萎縮性側索硬化症標籤
07:13
I'm taking three drugs to manage it. Some of them are experimental.
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我吃三種藥﹐一些還在實驗階段
07:16
I can look at my constipation, how to manage it.
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我該怎麼解決我的便秘問題
07:18
I can see magnesium citrate, and the side effects
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檸檬酸鎂和它的副作用
07:20
from that drug all integrated in the time
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在它的有效期之內
07:22
in which they're meaningful.
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它做了什麼
07:25
But I want more.
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我還想要更多
07:27
I don't want to just look at this cool device, I want to take this
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我不想只是看看這些功能
07:29
data and make something even better.
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我希望能用這些數據改善現狀
07:31
I want my brother's center of the universe and his symptoms
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我要我弟弟的狀況﹐病症
07:34
and his drugs,
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他的用藥
07:37
and all of the things that interact among those,
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副作用﹐所有這些資訊
07:39
the side effects, to be in this beautiful data galaxy
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放進這個美麗的數據銀河
07:42
that we can look at in any way we want to understand it,
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就可以用它來做很多研究
07:45
so that we can take this information
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我們可以利用這些資料
07:48
and go beyond just this simple model
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超越過去的記錄模式
07:52
of what a record is.
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.
07:55
I don't even know what a medical record is.
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我甚至不知道醫療記錄是什麼
07:57
I want to solve a problem. I want an application.
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我祇想解決問題﹐我想要一個應用程式
07:59
So, can I take this data -- rearrange yourself,
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我把這些數據﹐你自己可以調整
08:02
put the symptoms in the left, the drugs across the top,
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把症狀放在左邊﹐藥物放上面
08:04
tell me everything we know about Steven and everyone else,
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這可以告訴我們有關 Steven 和所有人的資料
08:06
and what interacts.
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哪些重複了
08:09
Years after he's had these drugs,
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在他用這些藥的多年以後
08:11
I learned that everything he did to manage his excess saliva,
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我終於知道他為了控制唾液
08:14
including some positive side effects that came from other drugs,
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和其他一些藥的副作用
08:17
were making his constipation worse.
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惡化了他的便秘問題
08:19
And if anyone's ever had severe constipation,
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如果有人曾經有過嚴重便秘
08:21
and you don't understand how much of an impact that has on your life --
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你不了解這對你生活的影響有多大
08:23
yes, that was a pun.
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這是一個雙關語
08:26
You're trying to manage these,
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你嘗試去理解這些
08:28
and this grid is available here,
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這個表格就在這裡
08:30
and we want to understand it.
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我們想要了解
08:33
No one's ever had this kind of information.
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在這之前從來沒有人擁有這些資料
08:36
So, patients have this. We're for patients.
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這是為了病患做的
08:38
This is all about patient health care, there was no doctors on our network.
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病患分享他們的醫療經驗﹐這裡沒有駐站醫生
08:40
This is about the patients.
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全是病患自己
08:42
So, how can we take this and bring them a tool
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我們該如何使用這些資料
08:45
that they can go back and they can engage the medical system?
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讓病患可以把這些資料帶回他們所使用的醫療系統﹖
08:47
And we worked hard, and we thought about it and we said,
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我們努力的思考﹐我們想
08:50
"What's something we can use all the time,
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“什麼是我們現在的醫療系統中
08:52
that we can use in the medical care system,
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所使用﹐而且每個人
08:54
that everyone will understand?"
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都明白的﹖”
08:56
So, the patients print it out,
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於是病患把它印出來
08:58
because hospitals usually block us
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因為醫院拒絕我們
09:00
because they believe we are a social network.
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他們覺得我們只是網路社群
09:03
It's actually the most used feature on the website.
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這是網站上最多人使用的功能
09:05
Doctors actually love this sheet, and they're actually really engaged.
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醫生們喜歡這個資料﹐他們非常投入
09:08
So, we went from this story of Steven
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於是我們從 Steven 的故事
09:11
and his history to data, and then back to paper,
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把故事化為數據﹐然後回到紙上
09:14
where we went back and engaged the medical care system.
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然後回到我們的醫療系統
09:15
And here's another paper.
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這是另外一種紙
09:17
This is a journal, PNAS --
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這是《國家科学院院刊》
09:19
I think it's the Proceedings of the National Academy of Science
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這是美國國家科學院裡的
09:21
of the United States of America.
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一項刊物
09:23
You've seen multiple of these today, when everyone's bragging about
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你今天已經看到它幾次了﹐每個人都在吹噓
09:25
the amazing things they've done.
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他們做的了不起的事情
09:27
This is a report about a drug called lithium.
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這裡有個關於鋰這個藥物的報告
09:29
Lithium, that is a drug used to treat bipolar disorder,
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鋰本來是用來治療躁鬱症的
09:33
that a group in Italy found
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意大利的一個團體發現
09:35
slowed ALS down in 16 patients, and published it.
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它減緩了16個肌肉萎縮性側索硬化症的症狀﹐就發表了這篇文章
09:38
Now, we'll skip the critiques of the paper.
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我們先不批評這個期刊
09:40
But the short story is: If you're a patient,
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簡單的說﹐如果你是病患
09:42
you want to be on the blue line.
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你想在藍線上
09:44
You don't want to be on the red line, you want to be on the blue line.
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你不想在紅線上﹐你想在藍線上
09:46
Because the blue line is a better line. The red line
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因為藍線比較好﹐紅線
09:48
is way downhill, the blue line is a good line.
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在下面﹐藍線是好的
09:50
So, you know we said -- we looked at this, and what I love also
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我們看著這個﹐我覺得那些
09:54
is that people always accuse these Internet sites
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批評網路不負責任地廣告藥物
09:56
of promoting bad medicine and having people do things irresponsibly.
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讓人們做出錯誤決定的人也很有趣
09:59
So, this is what happened when PNAS published this.
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當《國家科学院院刊》發表這篇文章以後
10:02
Ten percent of the people in our system took lithium.
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我們系統裡有一成的人開始使用鋰
10:05
Ten percent of the patients started taking lithium based on 16 patients of data
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一成的病患因為16個病患的醫療結果開始使用鋰
10:08
in a bad publication.
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因為這個錯誤的報告
10:10
And they call the Internet irresponsible.
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他們卻說網路不負責任
10:12
Here's the implication of what happens.
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這就是事情發生的經過
10:14
There's this one guy, named Humberto, from Brazil,
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有個名叫 Humberto 的巴西人
10:17
who unfortunately passed away nine months ago,
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他在九個月前過世了
10:20
who said, "Hey, listen. Can you help us answer this question?
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他說“聽著﹐你可以幫我們回答這個問題嗎﹖
10:22
Because I don't want to wait for the next trial, it's going to be years.
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因為我不想等下次實驗結束﹐那還得等上多年
10:25
I want to know now. Can you help us?"
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我現在就要知道﹐你可以幫助我嗎﹖”
10:27
So, we launched some tools, we let them track their blood levels.
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於是我們增加一些功能﹐讓他們追蹤血液質
10:30
We let them share the data and exchange it.
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互相分享交換數據
10:32
You know, a data network.
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一個數據網
10:35
And they said, you know, "Jamie, PLM,
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然後他們說“我們可以把產品生命週期管理的概念
10:37
can you guys tell us whether this works or not?"
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運用在這裡嗎 ? ”
10:39
And we went around and we talked to people,
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於是我們四處問人
10:41
and they said, "You can't run a clinical trial like this. You know?
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他們說“你不能這樣做臨床測試
10:43
You don't have the blinding, you don't have data,
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你們沒有雙盲測試﹐沒有數據
10:45
it doesn't follow the scientific method.
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這沒有任何科學方法
10:47
It's never going to work. You can't do it."
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這不行﹐你不能這樣做。”
10:49
So, I said, "Okay well we can't do that. Then we can do something harder."
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於是我說“好吧我們不做這個﹐我們做一些更困難的。”
10:52
(Laughter)
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(笑聲)
10:55
I can't say whether lithium works in all ALS patients,
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我不知道鋰在肌肉萎縮性側索硬化症患者身上是否都管用
10:57
but I can say whether it works in Humberto.
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但我知道它在 Humberto 身上是否管用
11:00
I bought a Mac about two years ago, I converted over,
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兩年前我把電腦換成蘋果
11:02
and I was so excited about this new feature of the time machine
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我對“時間機器”這個功能非常興奮
11:04
that came in Leopard. And we said -- because it's really cool,
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真的很酷
11:06
you can go back and you can look at the entire history of your computer,
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你可以回顧電腦裡的所有歷史
11:08
and find everything you've lost, and I loved it.
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找到所有消失的資料﹐我非常喜歡
11:10
And I said, "What if we built a time machine for patients,
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我說“我們可以為患者做一個時間機器嗎
11:14
except instead of going backwards, we go forwards.
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但不是往回看﹐而是往未來前進
11:17
Can we find out what's going to happen to you,
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我們可以知道他們的病將會如何發展
11:20
so that you can maybe change it?"
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或許可以改變這個結果﹖”
11:23
So, we did. We took all the patients like Humberto,
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於是我們聚集了所有病患資料
11:26
That's the Apple background, we stole that because we didn't have time
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這個背景是蘋果的﹐因為我們沒有時間做自己的背景
11:28
to build our own. This is a real app by the way.
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這是一個真正的應用程式
11:30
This is not just graphics.
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不只是圖表
11:32
And you take those data, and we find the patients like him, and we bring
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把所有病患,像他的病患
11:34
their data together. And we bring their histories into it.
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把他們的患病過程放進去
11:38
And then we say, "Well how do we line them all up?"
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我們想“我們該怎麼排列它們? ”
11:40
So, we line them all up so they go together
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於是我們把他們放在一起
11:42
around the meaningful points,
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在那些有意義的數據點上
11:44
integrated across everything we know about the patient.
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綜合所有有關這個病患的訊息
11:46
Full information, the entire course of their disease.
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他們完整的病史
11:50
And that's what is going to happen to Humberto,
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這就是 Humberto 將要面對的病情
11:52
unless he does something.
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除非他做了別的措施
11:54
And he took lithium, and he went down the line.
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他吃了鋰﹐他的線往下掉
11:57
And it works almost every time.
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這幾乎百發百中
12:00
Now, the ones that it doesn't work are interesting.
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那些於別人不同的曲線圖很有趣
12:02
But almost all the time it works.
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但幾乎毫無例外
12:05
It's actually scary. It's beautiful.
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它準確地令我們害怕
12:07
So, we couldn't run a clinical trial, we couldn't figure it out.
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我們不能做臨床實驗﹐我們不能完全理解
12:09
But we could see whether it was going to work for Humberto.
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但我們可以知道它在 Humberto 身上是否管用
12:12
And yeah, all the clinicians in the audience will talk about power
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我們知道在場的醫生會談到統計效力
12:14
and all the standard deviation. We'll do that later.
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和標準差﹐我們晚點會提到
12:16
But here is the answer
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但答案在這裡
12:20
of the mean of the patients that actually decided
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這是那些決定使用鋰的病人的
12:22
to take lithium.
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平均值
12:24
These are all the patients that started lithium.
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這些是全部使用鋰的病患
12:26
It's the Intent to Treat Curve.
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這是他們的治療曲線
12:28
You can see here, the blue dots on the top, the light ones,
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你也可以看到﹐上面淡淡的藍點
12:32
those are the people in the study in PNAS
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是《國家科学院院刊》裡的病患
12:34
that you wanted to be on. And the red ones are the ones,
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也是人們想要得到的結果
12:36
the pink ones on the bottom are the ones you didn't want to be.
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下面的粉色點則是你不想要的結果
12:38
And the ones in the middle are all of our patients
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中間的就是我們的病患
12:41
from the start of lithium at time zero,
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從開始服用鋰開始
12:43
going forward, and then going backward.
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繼續﹐然後繼續
12:47
So, you can see we matched them perfectly, perfectly.
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你可以看見這些數據完美的一致
12:50
Terrifyingly accurate matching.
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恐怖地相同
12:52
And going forward, you actually don't want to be a lithium patient this time.
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繼續下去﹐你就不希望自己是個服用鋰的病人了
12:56
You're actually doing slightly worse -- not significantly,
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病情開始稍微惡化﹐雖然不是很嚴重
12:58
but slightly worse. You don't want to be a lithium patient this time.
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但稍微惡化﹐你不想是服用鋰的病人了
13:01
But you know, a lot of people dropped out,
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但許多人放棄繼續
13:04
the trial, there is too much drop out.
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做完這個實驗
13:06
Can we do the even harder thing? Can we go to the patients
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我們是否能找到那些
13:08
that actually decided to stay on lithium,
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繼續服用鋰的病人
13:12
because they were so convinced they were getting better?
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因為他們認為他們的病情已經開始好轉
13:14
We asked our control algorithm,
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我們控制算法的結果是
13:16
are those 69 patients -- by the way, you'll notice
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這69個病人
13:18
that's four times the number of patients in the clinical trial --
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也就是接受臨床實驗的四倍
13:21
can we look at those patients and say,
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我們看這些病患﹐然後說
13:24
"Can we match them with our time machine
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“我們可以把他們放進我們的時間機器
13:27
to the other patients that are just like them,
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和其他的病患比較一下
13:29
and what happens?"
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看看會有什麼結果”
13:31
Even the ones that believed they were getting better
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結果是就算他們相信自己的病情好轉了
13:34
matched the controls exactly. Exactly.
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事實上卻和一樣。
13:37
Those little lines? That's the power.
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這些線是什麼﹖這就是統計效力
13:39
So, we -- I can't tell you lithium doesn't work. I can't tell you
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我不能告訴你鋰不管用
13:41
that if you did it at a higher dose
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我不能說如果你用更高劑量
13:43
or if you run the study proper -- I can tell you
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和你再做其他實驗﹐但我可以告訴你
13:45
that for those 69 people that took lithium,
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那服用鋰的69人
13:49
they didn't do any better than the people that were just like them,
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他們的病情沒有改善
13:51
just like me,
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就像我一樣
13:53
and that we had the power to detect that at about
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我們有統計效力可以測試
13:56
a quarter of the strengths reported in the initial study.
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原本的報告只有四分之一
13:59
We did that one year ahead of the time
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我們比國家研究院贊助百萬的
14:02
when the first clinical trial funded by the NIH
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臨床實驗還要早一年開始
14:04
for millions of dollars failed for futility last week,
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上個禮拜他們公佈了他們的失敗
14:07
and announced it.
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.
14:10
So, remember I told you about my brother's stem cell transplant.
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記得我弟的幹細胞移植嗎
14:13
I never really knew whether it worked.
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我不知道那管不管用
14:16
And I put 100 million cells in his cisterna magna,
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我在他的小腦延髓池和腰椎
14:19
in his lumbar cord,
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植入了一億個細胞
14:21
and filled out the IRBs and did all this work,
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填了一個同意臨床試驗證明書﹐做了這些
14:23
and I never really knew.
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但我從來沒有真正知道
14:26
How did I not know?
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我怎麼可能不知道﹖
14:28
I mean, I didn't know what was going to happen to him.
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我甚至不知道這樣會發生什麼
14:30
I actually asked Tim, who is the quant in our group --
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於是我問 Tim﹐我們這組人的數據分析師
14:33
we actually searched for about a year to find someone
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我們找了一整年才找到
14:36
who could do the sort of math and statistics and modeling
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一個可以算這些統計﹐這些模型的人
14:38
in healthcare, couldn't find anybody. So, we went to the finance industry.
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在醫界我們一個也找不到﹐於是我們到金融界找
14:41
And there are these guys who used to model the future
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這些人擅於預測未來的利率
14:43
of interest rates, and all that kind of stuff.
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那些所有的東西
14:45
And some of them were available. So, we hired one.
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某些人突然有空了﹐於是我們請了一個
14:48
(Laughter)
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(笑聲)
14:51
We hired them, set them up, assisting at lab.
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我們請他們來﹐請他們幫助我們的實驗室
14:53
I I.M. him things. That's the way I communicate with him,
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把東西在網上用即時通寄給他
14:55
is like a little guy in a box. I I.M.ed Tim. I said,
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像個盒子裡的小人﹐我在即時通上問他﹕
14:57
"Tim can you tell me whether my brother's stem cell transplant
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“Tim 你可以告訴我﹐我弟的幹細胞移植
14:59
worked or not?"
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到底有沒有用? ”
15:02
And he sent me this two days ago.
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於是兩天前﹐他寄了這個給我
15:05
It was that little outliers there. You see that guy that lived a long time?
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你看到這個異常值了嗎﹖有個男人活了很長時間﹖
15:08
We have to go talk to him. Because I'd like to know what happened.
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我們得去和他聊聊﹐因為我想知道他做了什麼
15:10
Because something went different.
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他一定做了一些不同的事
15:12
But my brother didn't. My brother went straight down the line.
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因為我弟弟沒有。我弟弟的線掉下去了
15:15
It only works about 12 months.
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支撐了十二個月
15:17
It's the first version of the time machine.
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這是時間機器的第一個版本
15:19
First time we ever tried it. We'll try to get it better later
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我們第一次嘗試﹐我們會嘗試改進
15:21
but 12 months so far.
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十二個月了
15:24
And, you know, I look at this,
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當我看到這個
15:28
and I get really emotional.
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我心裡很激動
15:30
You look at the patients, you can drill in all the controls,
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你看著這些病患﹐你可以比較所有的對照值
15:32
you can look at them, you can ask them.
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你看著他們﹐你問他們
15:34
And I found a woman that had --
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我找到一個女人
15:37
we found her, she was odd because she had data
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因為她的數據很奇怪
15:39
after she died.
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在死後還有數據
15:41
And her husband had come in and entered her last functional scores,
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他的丈夫在她死後登錄﹐輸入她最後的狀況
15:44
because he knew how much she cared.
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因為他知道她很在乎
15:47
And I am thankful.
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我很感謝他
15:50
I can't believe that these people,
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我不敢相信這些人
15:52
years after my brother had died,
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在我弟弟死後這麼多年
15:54
helped me answer the question about whether
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告訴我多年前我做的這個手術
15:56
an operation I did, and spent millions of dollars on
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這個花了幾百萬的手術
15:59
years ago, worked or not.
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究竟有沒有用
16:01
I wished it had been there
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我希望當時就有這個網站
16:03
when I'd done it the first time,
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在我當時開始做得時候
16:05
and I'm really excited that it's here now,
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我真的很興奮現在我們有了這個功能
16:07
because the lab that I founded
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因為在這個實驗室裡
16:12
has some data on a drug that might work,
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我們找到了一些數據﹐顯示某個藥可能有用
16:14
and I'd like to show it.
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我希望展示給你們看
16:18
I'd like to show it in real time, now,
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現在
16:20
and I want to do that for all of the diseases that we can do that for.
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我希望為所有的病都做到
16:25
I've got to thank the 45,000 people
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我要謝謝這四萬五千個人
16:28
that are doing this social experiment with us.
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和我們一起進行這次社群實驗
16:31
There is an amazing journey we are going on
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我們一起在一個神奇的路途上
16:34
to become human again,
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找回我們的人性
16:36
to be part of community again,
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重新成為一個社群
16:39
to share of ourselves, to be vulnerable,
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分享我們自己的脆弱
16:41
and it's very exciting. So, thank you.
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這是很令人興奮的。謝謝大家。
16:44
(Applause)
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(掌聲)
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