Artificial intelligence for global health.

Artificial intelligence for global health.
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DOI:
10.1126/science.aay5189
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发表时间:
2019-11-22
期刊:
Science (New York, N.Y.)
影响因子:
--
通讯作者:
Aerts HJWL
Aerts HJWL
中科院分区:
其他
文献类型:
--
作者:
Hosny A;Aerts HJWL

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人工智能(AI)在疾病的检测、诊断和治疗方面取得了巨大进展。深度学习是基于人工神经网络的机器学习的一个子集,它使应用程序的性能水平接近训练有素的专业人员,包括医学图像的解释和药物化合物的发现(1)。毫不奇怪,医疗保健领域的大多数人工智能开发都迎合了高收入国家(HIC)的需求,而大部分研究都是在高收入国家进行的。相反,很少有人讨论人工智能可以为低收入和中等收入国家(LMIC)的医疗实践带来什么,在这些国家,劳动力短缺和有限的资源限制了医疗服务的获取和质量。人工智能可以在解决个体患者、卫生系统和人口层面的全球医疗不平等方面发挥重要作用。然而,开发和实施人工智能应用程序的挑战必须在广泛采用和可衡量的影响之前得到解决。
Artificial intelligence (AI) has demonstrated great progress in the detection, diagnosis, and treatment of diseases. Deep learning, a subset of machine learning based on artificial neural networks, has enabled applications with performance levels approaching those of trained professionals in tasks including the interpretation of medical images and discovery of drug compounds (1). Not surprisingly, most AI developments in health care cater to the needs of high-income countries (HICs), where the majority of research is conducted. Conversely, little is discussed about what AI can bring to medical practice in low- and middle-income countries (LMICs), where workforce shortages and limited resources constrain the access to and quality of care. AI could play an important role in addressing global health care inequities at the individual patient, health system, and population levels. However, challenges in developing and implementing AI applications must be addressed ahead of widespread adoption and measurable impact.
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