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待翻译:Can AI really predict cancer survival better than a doctor? I have my doubts | Devi Sridhar

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AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:Take a selfie to see how healthy you are: the idea is enticing and this new research is promising. But so many factors have been ignored The idea that a single selfie could predict how long someone with cancer may live sounds like an incredible breakthrough. AI is getting better at spotting patterns in medical data, but can it be used to reliably predict what will happen to an individual patient? I asked a clinical colleague what she thought about the recent headlines. She found it an interesting development given that doctors have long used facial appearance to assess patient health. For example, she noted that they may write “appears stated age” or “appears older than stated age” as a proxy for general health. Now, researchers from Mass General Brigham, a hea…

来源The Guardian AI作者: Devi Sridhar
待翻译:Can AI really predict cancer survival better than a doctor? I have my doubts | Devi Sridhar
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AI 服务暂时不可用,以下为来源正文,待恢复后补全翻译。

Take a selfie to see how healthy you are: the idea is enticing and this new research is promising. But so many factors have been ignored The idea that a single selfie could predict how long someone with cancer may live sounds like an incredible breakthrough. AI is getting better at spotting patterns in medical data, but can it be used to reliably predict what will happen to an individual patient? I asked a clinical colleague what she thought about the recent headlines. She found it an interesting development given that doctors have long used facial appearance to assess patient health. For example, she noted that they may write “appears stated age” or “appears older than stated age” as a proxy for general health. Now, researchers from Mass General Brigham, a healthcare institution in Massachusetts, have taken this idea a step further. They have developed an AI model trained on more than 40 million facial images – called FAHR-Face – to assess biological age and predict survival in cancer patients. For biological age, they developed FAHR-FaceAge, which estimates age from certain facial features such as the forehead, the wrinkles between the nose and mouth and the temples. For cancer survival, they developed FAHR-FaceSurvival, trained using almost 35,000 photos of cancer patients. This model focused more closely on the area below the eyes and the bridge of the nose – regions of the face “linked with dying”. Dr Raymond Mak, one of the study’s authors, noted that these parts of the face are the same as those referenced by Hippocrates in 400BC as signs of muscle wasting and mortality risk: “the nose sharp, the eyes sunken, the temples fallen in”. Prof Devi Sridhar is chair of global public health at the University of Edinburgh Continue reading...

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  • Take a selfie to see how healthy you are: the idea is enticing and this new research is promising. But so many factors have been ignored The idea that a single selfie could predic…

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