AIMC Topic: Healthcare Disparities
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Deep transfer learning for reducing health care disparities arising from biomedical data inequality.
Nature communications
Oct 12, 2020
As artificial intelligence (AI) is increasingly applied to biomedical research and clinical decisions, developing unbiased AI models that work equally well for all ethnic groups is of crucial importance to health disparity prevention and reduction. H...
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Epilepsia
Aug 23, 2019
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm trained on physician notes would produce biased recommendations for epilepsy presurgical evaluation...
Can AI Help Reduce Disparities in General Medical and Mental Health Care?
AMA journal of ethics
Feb 1, 2019
BACKGROUND: As machine learning becomes increasingly common in health care applications, concerns have been raised about bias in these systems' data, algorithms, and recommendations. Simply put, as health care improves for some, it might not improve ...
Ensuring Fairness in Machine Learning to Advance Health Equity.
Annals of internal medicine
Dec 4, 2018
Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and struct...
Disparities in the Treatment and Outcome of Stage I Non-Small-Cell Lung Cancer in the 21st Century.
Clinical lung cancer
Nov 20, 2018
BACKGROUND: African American (AA) individuals are less likely to receive treatment and more likely to die from cancer compared with Caucasian (C) individuals. Recent advancements in surgery and radiation have improved outcomes in early stage non-smal...
Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.
Journal of diabetes science and technology
Sep 5, 2018
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...
Phenotype
Precision Medicine
Language
Reproducibility of Results
Public Health
Big Data
Decision Support Systems, Clinical
Humans
Artificial Intelligence
Diabetes Mellitus, Type 1
Decision Making
Ethnicity
Healthcare Disparities
Data Collection
Access to Information
Racial Groups
Diabetes Mellitus, Type 2
Genotype
Computational Biology
Update: healthcare reform - it's getting personal.
Personalized medicine
Jun 22, 2017
Using the Knowledge Base of Health Services Research to Redefine Health Care Systems.
Journal of general internal medicine
Apr 4, 2015
This Perspective discusses 12 key facts derived from 50 years of health services research and argues that this knowledge base can stimulate innovative thinking about how to make health care systems safer, more efficient, more cost effective, and more...
Biased AI: A Case for Positive Bias in Healthcare AI.
Studies in health technology and informatics
Aug 7, 2025
Bias in artificial intelligence (AI) is a pervasive challenge, often reinforcing systemic inequities in healthcare systems. This paper proposes an innovative framework to repurpose bias in AI, leveraging it as a tool for addressing structural injusti...
Incorporating machine learning and statistical methods to address maternal healthcare disparities in US: A systematic review.
International journal of medical informatics
Aug 1, 2025
BACKGROUND: Maternal health disparities are recognized as a significant public health challenge, with pronounced disparities evident across racial, socioeconomic, and geographic dimensions. Although healthcare technologies have advanced, these dispar...
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