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. 2019 Sep;211(5):203-205.e1.
doi: 10.5694/mja2.50294. Epub 2019 Aug 6.

Machine learning in clinical practice: prospects and pitfalls

Ian A Scott  1   2 , David Cook  1 , Enrico W Coiera  3 , Brent Richards  4
Affiliations

Machine learning in clinical practice: prospects and pitfalls

Ian A Scott et al. Med J Aust. 2019 Sep.
No abstract available

Keywords: Biostatistics; Clinical decision-making; Computing methodologies; Delivery of healthcare; Models, statistical; Technology.

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References

    1. Esteva A, Robicquet A, Ramsundar B, et al. A guide to deep learning in healthcare. Nature Med 2019; 25: 24-29.
    1. Naylor CD. On the prospects for a (deep) learning health care system. JAMA 2018; 320: 1099-1100.
    1. Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med 2019; 380: 1347-1358.
    1. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nature Med 2019; 25: 44-56.
    1. Ting DSW, Cheung CY-L, Lim G, et al. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA 2017; 318: 2211-2223.

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