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machine learning

Clinical significance: - machine learning algorithms detected diabetic retinopathy from retinal fundus photographs with > 87% sensitivity & specificity [1] - some of the ethical challenges inherent in implementing machine learning in health care may be straightforward, whereas others may have less obvious risks but raise broader ethical concerns - machine learning can be useful for developing disease models from big data when it is not known in advance which variables are important [3] - a large-scale screen employing machine learning yielded 8 potential antibiotics with new mechanisms of action [4]

General

learning artificial intelligence (AI)

References

  1. Gulshan V, Peng L,Coram M et al Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA. Published online November 29, 2016. PMID: 27898976 http://jamanetwork.com/journals/jama/fullarticle/2588763 - Wong TY, Bressler NM Artificial Intelligence With Deep Learning Technology Looks Into Diabetic Retinopathy Screening. JAMA. Published online November 29, 2016. PMID: 27898977 http://jamanetwork.com/journals/jama/fullarticle/2588762 - Beam AL, Kohane IS. Translating Artificial Intelligence Into Clinical Care. JAMA. Published online November 29, 2016. PMID: 27898974 http://jamanetwork.com/journals/jama/fullarticle/2588761 - Jha S, Topol EJ Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists. JAMA. Published online November 29, 2016. PMID: 27898975 http://jamanetwork.com/journals/jama/fullarticle/2588764
  2. Char DS, Shah NH, Magnus D. Implementing Machine Learning in Health Care - Addressing Ethical Challenges. N Engl J Med 2018; 378:981-983. March 15, 2018 PMID: 29539284 http://www.nejm.org/doi/full/10.1056/NEJMp1714229
  3. Beam AL, Kohane IS Big Data and Machine Learning in Health Care. JAMA. 2018;319(13):1317-1318. April 3, 2018 PMID: 29532063 https://jamanetwork.com/journals/jama/fullarticle/2675024
  4. Stokes JM et al. A deep learning approach to antibiotic discovery. Cell 2020 Feb 20; 180:688 PMID: 32084340