人工智能已經(jīng)展現(xiàn)出了幫助醫(yī)生預(yù)測病人是否易患阿爾茨海默?。ˋlzheimer’s）等慢性疾病的前景。

不過，在上周三圣迭戈舉辦的《財富》頭腦風暴健康大會（Fortune’s Brainstorm Health conference）上，輝瑞制藥（Pfizer）的副總裁和基因組科技部門主管莫滕·瑟高表示，盡管醫(yī)療業(yè)發(fā)展迅速，但在推出人工智能療法和藥品上還仍然處于初期階段。

瑟高表示，輝瑞多年來都在利用機器學習等人工智能技術(shù)篩選數(shù)據(jù)，幫助研究新藥配方（尤其是多種藥物的組合），并確定臨床試驗的最佳參與者。他在會上談到人工智能時說：“在一些情況下，這沒什么新鮮的?！?/p>

然而，他解釋道，新鮮之處在于越來越大的數(shù)據(jù)洪流，如醫(yī)療設(shè)備獲取的基因組數(shù)據(jù)和傳感器數(shù)據(jù)。這種數(shù)據(jù)流讓我們更難理清隱藏在其中的關(guān)鍵聯(lián)系，從而幫助研究人員發(fā)現(xiàn)新療法。

目前，輝瑞使用了深度學習來挖掘電子健康記錄和實驗室數(shù)據(jù)。這種方法曾因谷歌（Google）用以訓(xùn)練計算機識別照片中的貓而流行起來。瑟高表示，輝瑞可以借此更好地了解自體免疫和脂肪肝等疾病的進展。

瑟高稱，這些深度學習技術(shù)已經(jīng)展現(xiàn)了在大規(guī)模人群中尋找疾病模式的前景，不過最終的目標是幫助個體病人。

輝瑞還與IBM合作，利用其沃森（Watson）的數(shù)據(jù)處理技術(shù)進行藥學研究。公司同時也在與谷歌、亞馬遜（Amazon）和其他云計算供應(yīng)商合作，采用他們的對應(yīng)技術(shù)。

瑟高相信，許多云計算供應(yīng)商在未來都會擁有可供醫(yī)藥公司研究和開發(fā)使用的人工智能技術(shù)。不過他也表示：“當然，這不會在短期內(nèi)發(fā)生。”

該領(lǐng)域的迅速創(chuàng)新總有一天能夠幫助人類利用基因組、蛋白質(zhì)和醫(yī)學成像數(shù)據(jù)預(yù)測和診斷疾病，而聯(lián)邦法規(guī)目前還沒有跟上創(chuàng)新的步伐。不過瑟高對此充滿希望。根據(jù)輝瑞與監(jiān)管者的會面，他認為聯(lián)邦藥品管理局（Federal Drug Administration）在人工智能輔助醫(yī)學治療方面“很開明”。（財富中文網(wǎng)）

譯者：嚴匡正

Artificial intelligence has shown promise in helping doctors predict which patients may be susceptible to chronic diseases like Alzheimer’s.

But despite the rapid advances, the healthcare industry is still in the early days of rolling out AI-powered treatments and drugs, Morten Sogaard, Pfizer’s vice president and head of genome sciences and technologies, said at Fortune’s Brainstorm Health conference in San Diego on Wednesday.

Pfizer (pfe, -0.42%) has been using AI techniques like machine learning for years to sift through data, help research new drug compounds (essentially the combination of multiple drugs), and determine the best participants for clinical trials, he said. “In some cases, it is nothing new,” Sogaard said about AI in healthcare.

What is new, however, is the rising flood of information like genomic data and sensor data from medical devices, he explained. This influx has made it more difficult to understand key connections that could help researchers discover new treatments.

Currently, Pfizer is using deep learning, which Google (goog, +1.04%) helped to popularize as a way to train computers to recognize cats in photos, to mine electronic health records and lab data. By doing so, Pfizer can better understand how ailments like autoimmune and fatty liver diseases progress, he explained.

Sogaard said that these deep learning techniques have shown promise in finding disease patterns across large groups of people, but the ultimate goal is to eventually help individual patients.

Pfizer has also partnered with IBM (ibm, -0.30%) to use its Watson data-crunching technology in pharmaceutical research. But the company is also open to partnering with Google, Amazon (amzn, -0.62%), and other cloud-computing providers to incorporate their own respective technologies.

Sogaard believes a handful of cloud computing providers will have AI technologies that drug companies could eventually use for research and development. However, “it will not all happen the day after tomorrow, of course,” he said.

Federal regulations have not yet caught up to the rapid pace of innovation that could one day help predict and diagnose diseases using a combination of genomic, protein, and medical imaging data. But Sogaard is hopeful, and based on Pfizer’s meetings with regulators, he believes the Federal Drug Administration is “open-minded” to AI-assisted medical treatment.