AIMC Topic: Healthcare Disparities

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Ensuring Fairness in Machine Learning to Advance Health Equity.

Annals of internal medicine
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
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
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 ...

Using the Knowledge Base of Health Services Research to Redefine Health Care Systems.

Journal of general internal medicine
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...

Evaluating ChatGPT's Utility in Addressing Socioeconomic Disparities in Burn Patients: A Comparative Study With Google.

Journal of burn care & research : official publication of the American Burn Association
Patients from low-socioeconomic status (SES) backgrounds face barriers to quality burn care, such as limited healthcare access and follow-up. Many turn to online resources like Google, which may provide overwhelming or irrelevant information. This st...

Biased AI: A Case for Positive Bias in Healthcare AI.

Studies in health technology and informatics
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
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...

Enhancing neuro-oncology care through equity-driven applications of artificial intelligence.

Neuro-oncology
The disease course and clinical outcome for brain tumor patients depend not only on the molecular and histological features of the tumor but also on the patient's demographics and social determinants of health. While current investigations in neuro-o...

Estimation of racial and language disparities in pediatric emergency department triage using statistical modeling and natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting.