Indian Journal of Dermatology
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Year : 2020  |  Volume : 65  |  Issue : 5  |  Page : 358-364

The ethics of machine learning in medical sciences: Where do we stand today?

1 Department of Mathematics, Occidental College, Los Angeles, USA
2 Systems Biotechnology Group, Technical University of Munich, Boltzmannstr- 15, Garching, Germany
3 Department of Geography, University of California, Santa Barbara; Technology Department, Retirement Solutions Division, Pacific Life, Newport Beach, CA, USA

Correspondence Address:
Olaf Menzer
Department of Geography, University of California, Santa Barbara, California
Treena Basu
Department of Mathematics, Occidental College, 1600 Campus Road, Los Angeles
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijd.IJD_419_20

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Advances in Machine Learning and availability of state-of-the-art computational resources, along with digitized healthcare data, have set the stage for extensive application of artificial intelligence in the realm of diagnosis, prognosis, clinical decision support, personalized treatment options, drug development, and the field of biomedicine. Here, we discuss the application of Machine Learning algorithms in patient healthcare and dermatological domains along with the ethical complexities that are involved. In scientific studies, ethical challenges were initially not addressed proportionally (as assessed by keyword counts in PubMed) and just more recently (since 2016) this has started to improve. Few pioneering countries have created regulatory guidelines around how to respect matters of (1) privacy, (2) fairness, (3) accountability, (4) transparency and (5) conflict of interest when developing novel medical Machine Learning applications. While there is a strong promise of emerging medical applications to ultimately benefit both the patients and the medical practitioners, it is important to raise awareness on the five key ethical issues and incorporate them into medical practice in the near future.

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