Digital Futures Past - The Long Arc of Big Data in Medicine.
Digital Futures Past - The Long Arc of Big Data in Medicine.
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DOI：
10.1056/nejmms1817674
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发表时间：
2019-08-01
期刊：
影响因子：
--
通讯作者：
Lea AS
中科院分区：
文献类型：
--
作者：
Greene JA;Lea AS
大数据可能是医学的未来，但也是过去。1964年，发明家弗拉基米尔·兹沃雷金警告说，医学数据的积累速度超过了医生的认知能力。Zworykin宣称，不仅医院记录和医学文献中的信息量“太大，任何一个人的记忆都无法涵盖”，而且传统的抽象、总结和索引技术也无法以一种在实践中容易获得的形式为医生提供所需的知识。幸运的是，数字计算机--从20世纪40年代房间大小的ENIAC到20世纪50年代冰箱大小的IBM大型机，再到20世纪60年代的“小型计算机”--可以以超人的速度部署算法搜索技术。“因此，”他总结道，“将电子记忆视为医生人类记忆的有效补充和延伸是非常合理的。”[1]半个世纪前，医生和工程师都有一个梦想，那就是拥有超大内存和超快处理时间的计算机可以推断诊断、存储医疗记录和传播信息。2.尽管当今的精准医疗、神经网络和可穿戴技术与“大型医疗”的世界相比，涉及到非常不同的对象、网络和用户，但许多基本问题仍然没有改变，而且并非所有数字医疗的挑战都能通过新技术来解决。3
Big data may be the future of medicine, but it is also its past. In 1964, the inventor Vladimir Zworykin warned that medical data were accumulating at a pace exceeding physicians’ cognitive capacity. Not only was the amount of information available in hospital records and medical literature “far too large to be encompassed by the memory of any single man,” Zworykin declared,“but the conventional techniques of abstracting, summarizing, and indexing cannot provide the physician with the needed knowledge in a form readily accessible in his practice.” Fortunately, the digital computer—which had shrunk from the room-sized ENIAC of the 1940s to the refrigerator-sized IBM mainframe of the 1950s to the “minicomputers” of the 1960s—could deploy algorithmic search techniques at superhuman speeds.“It is thus quite reasonable,” he concluded,“to think of electronic memories as effective supplements and extension of the human memory of the physician.” 1Half a century ago, physicians and engineers shared a dream that computers wielding ultravast memories and ultrafast processing times could deduce diagnoses, store medical records, and circulate information. 2 Though today’s world of precision medicine, neural nets, and wearable technologies involves very different objects, networks, and users than the world of “mainframe medicine” did, many fundamental problems remain unchanged—and not all challenges of digital medicine can be resolved by new technologies alone. 3