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Review
. 2022 Jan;28(1):31-38.
doi: 10.1038/s41591-021-01614-0. Epub 2022 Jan 20.

AI in health and medicine

Pranav Rajpurkar #  1 , Emma Chen #  2 , Oishi Banerjee #  2 , Eric J Topol  3
Affiliations
Review

AI in health and medicine

Pranav Rajpurkar et al. Nat Med. 2022 Jan.

Abstract

Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients. We discuss key findings from a 2-year weekly effort to track and share key developments in medical AI. We cover prospective studies and advances in medical image analysis, which have reduced the gap between research and deployment. We also address several promising avenues for novel medical AI research, including non-image data sources, unconventional problem formulations and human-AI collaboration. Finally, we consider serious technical and ethical challenges in issues spanning from data scarcity to racial bias. As these challenges are addressed, AI's potential may be realized, making healthcare more accurate, efficient and accessible for patients worldwide.

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References

    1. Gulshan, V. et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. J. Am. Med. Assoc. 316, 2402–2410 (2016). - DOI
    1. Esteva, A. et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 542, 115–118 (2017). - PubMed - PMC - DOI
    1. Rajpurkar, P. et al. Deep learning for chest radiograph diagnosis: a retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med. 15, e1002686 (2018). - PubMed - PMC - DOI
    1. Hannun, A. Y. et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat. Med. 25, 65–69 (2019). - PubMed - PMC - DOI
    1. Wiens, J. et al. Do no harm: a roadmap for responsible machine learning for health care. Nat. Med. 25, 1337–1340 (2019). - PubMed - DOI

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