TED演讲:你的用词透露了你未来的精神状态?(5)
时间：2018-10-06 00:24:59
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（单词翻译）
And it turned out to be that for this group of 34 people, 结果显示，刚刚的34位年轻人，
the algorithm based on semantic
coherence1 could predict, 透过这个语义连贯性算法，
with 100 percent accuracy, who developed psychosis and who will not. 预测谁会精神错乱的正确率达到百分之百。
And this was something that could not be achieved not even close 目前临床上所有测量方式都无法达到、
with all the other existing clinical measures. 或接近这个数字。
And I remember
vividly2, while I was working on this, 在我做这项研究的时候，清楚地记得一件事，
I was sitting at my computer and I saw a bunch of tweets by Polo 当时我坐在计算机前面，看到保罗传了一堆信息给我，
Polo had been my first student back in Buenos Aires, 他是之前我回到布宜诺斯艾利斯的第一个学生
and at the time he was living in New York. 当时他住在纽约。
And there was something in this tweets 我发现讯息不太对劲
I could not tell exactly what because nothing was said
explicitly3 虽然我讲不出个所以然来，因为他写得不清不楚
but I got this strong
hunch4, this strong intuition, that something was going wrong. 但我有一个强烈的直觉，一定是出事了。
So I picked up the phone, and I called Polo, and in fact he was not feeling well. 所以我打电话给保罗，没错，他当时感觉不太舒服。
And this simple fact, that reading in between the lines, 用这样一个单纯的辨认方式，从他的字里行间，
I could sense, through words, his feelings, was a simple, but very effective way to help. 我可以隐约感受到他的感觉，并在第一时间有效地帮助他。
What I tell you today is that we're getting close to understanding 今天我要告诉各位的是，我们已经越来越能理解
how we can convert this intuition that we all have, that we all share, into an algorithm. 如何把我们共有的直觉转换成算法。
And in doing so, we may be seeing in the future a very different form of mental health, 经由这样做，未来我们也许可以看到一种全然不同的心理健康模式，
based on objective,
quantitative5 and
automated6 analysis of the words we write, of the words we say. 而且是基于一种客观、量化的方式来自动分析出我们所写的字、我们所说的话。
Gracias. 谢谢。
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