AIMC Topic: Health Equity

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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...

[Health Equity in Mental Health Care: Challenges for Nurses and Related Preparation].

Hu li za zhi The journal of nursing
Individuals with mental illness face significant challenges in achieving health equity due to social and structural determinants, fragmented healthcare systems, social stigmas, and disparities in digital health access. As advocates for individuals wi...

Achieving SDoH Resource Equity in PICU Using an AI-Enabled Patient Navigator.

Studies in health technology and informatics
Trauma care coordination in the pediatric intensive care unit (PICU), including personalization of resources based on social determinants of health (SDoH), is challenging for already strained healthcare providers. Patient SDoH data collection is inco...

Artificial Intelligence in Cancer Care: Addressing Challenges and Health Equity.

Oncology (Williston Park, N.Y.)
Overdiagnosis in cancer care remains a significant concern, often resulting in unnecessary physical, emotional, and financial burdens on patients. Artificial intelligence (AI) has the potential to address this challenge by enabling more accurate, per...

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...

Fairness in Classifying and Grouping Health Equity Information.

Studies in health technology and informatics
This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health rec...

Toward an "Equitable" Assimilation of Artificial Intelligence and Machine Learning into Our Health Care System.

North Carolina medical journal
Enthusiasm about the promise of artificial intelligence and machine learning in health care must be accompanied by oversight and remediation of any potential adverse effects on health equity goals that these technologies may create. We describe five ...

Equity and AI governance at academic medical centers.

The American journal of managed care
OBJECTIVES: To understand whether and how equity is considered in artificial intelligence/machine learning governance processes at academic medical centers.