AIMC Topic: Healthcare Disparities
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Teaching yourself about structural racism will improve your machine learning.
Biostatistics (Oxford, England)
Apr 1, 2020
In this commentary, we put forth the following argument: Anyone conducting machine learning in a health-related domain should educate themselves about structural racism. We argue that structural racism is a critical body of knowledge needed for gener...
Rise of Robot Radiologists.
Nature
Dec 1, 2019
Cardiovascular Diseases
Diagnosis, Computer-Assisted
Deep Learning
Sensitivity and Specificity
Diagnostic Errors
Breast Neoplasms
Robotics
Radiology
Bias
United States
Mammography
Triage
Humans
Diabetic Retinopathy
Tomography, X-Ray Computed
Clinical Decision-Making
Female
Datasets as Topic
Retina
Practice Guidelines as Topic
Radiologists
Tuberculosis
Uncertainty
Healthcare Disparities
Confounding Factors, Epidemiologic
United States Food and Drug Administration
Cell Phone
A fairer way forward for AI in health care.
Nature
Sep 1, 2019
The Role of the ACR Data Science Institute in Advancing Health Equity in Radiology.
Journal of the American College of Radiology : JACR
Apr 1, 2019
Commercially available artificial intelligence (AI) algorithms outside of health care have been shown to be susceptible to ethnic, gender, and social bias, which has important implications in the development of AI algorithms in health care and the ra...
Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data.
JAMA internal medicine
Nov 1, 2018
A promise of machine learning in health care is the avoidance of biases in diagnosis and treatment; a computer algorithm could objectively synthesize and interpret the data in the medical record. Integration of machine learning with clinical decision...
Implementing Machine Learning in Health Care - Addressing Ethical Challenges.
The New England journal of medicine
Mar 15, 2018
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