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Big data and black-box medical algorithms

Published:2018-12-12 Issue:471 Volume:10 Page:
ISSN:1946-6234
Container-title:Science Translational Medicine
language:en
Short-container-title:Sci. Transl. Med.

Author:

Price W. Nicholson¹²³^ORCID

Affiliation:

1. University of Michigan Law School, 921 Legal Research, 801 Monroe St., Ann Arbor, MI 48109, USA.

2. Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics, Harvard Law School, 23 Everett St., Cambridge, MA 02138, USA.

3. Collaborative Research Program for Biomedical Innovation Law, University of Copenhagen Faculty of Law, Copenhagen, Denmark.

Abstract

New machine-learning techniques entering medicine present challenges in validation, regulation, and integration into practice.

Funder

National Cancer Institute

Novo Nordisk Fonden

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Medicine

Reference10 articles.

1. Predicting the Future — Big Data, Machine Learning, and Clinical Medicine

2. Dermatologist-level classification of skin cancer with deep neural networks

3. Development and validation of a machine learning algorithm and hybrid system to predict the need for life-saving interventions in trauma patients

4. Next generation phenotyping in Emanuel and Pallister-Killian syndrome using computer-aided facial dysmorphology analysis of 2D photos

5. Black-box medicine;Price W. N.;Harv. J. L. Tech.,2015

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