AIMC Topic: Primary Health Care

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Toward Automated Detection of Biased Social Signals from the Content of Clinical Conversations.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Implicit bias can impede patient-provider interactions and lead to inequities in care. Raising awareness is key to reducing such bias, but its manifestations in the social dynamics of patient-provider communication are difficult to detect. In this st...

Artificial Intelligence and Family Medicine.

Journal of the American Board of Family Medicine : JABFM
Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the practice of family medicine. The specialty is fortunate to have leading experts in the field to guide us along the way. One such team of forward thinkers...

Artificial intelligence in primary care practice: Qualitative study to understand perspectives on using AI to derive patient social data.

Canadian family physician Medecin de famille canadien
OBJECTIVE: To understand the perspectives of primary care clinicians and health system leaders on the use of artificial intelligence (AI) to derive information about patients' social determinants of health.

Developing an AI Tool to Derive Social Determinants of Health for Primary Care Patients: Qualitative Findings From a Codesign Workshop.

Annals of family medicine
PURPOSE: Information about social determinants of health (SDOH) is essential for primary care clinicians in the delivery of equitable, comprehensive care, as well as for program planning and resource allocation. SDOH are rarely captured consistently ...

What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care.

Journal of the American Board of Family Medicine : JABFM
Primary care physicians are likely both excited and apprehensive at the prospects for artificial intelligence (AI) and machine learning (ML). Complexity science may provide insight into which AI/ML applications will most likely affect primary care in...

Predicting Dementia Risk for Elderly Community Dwellers in Primary Care Services Using Subgroup-specific Prediction Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Early detection of individuals with a high risk of dementia is crucial for prompt intervention and clinical care. This study aims to identify high-risk groups for developing dementia by predicting the outcome of the Mini-Mental State Examination (MMS...

Analysis of 'One in a Million' primary care consultation conversations using natural language processing.

BMJ health & care informatics
BACKGROUND: Modern patient electronic health records form a core part of primary care; they contain both clinical codes and free text entered by the clinician. Natural language processing (NLP) could be employed to generate these records through 'lis...

Artificial intelligence and health inequities in primary care: a systematic scoping review and framework.

Family medicine and community health
OBJECTIVE: Artificial intelligence (AI) will have a significant impact on healthcare over the coming decade. At the same time, health inequity remains one of the biggest challenges. Primary care is both a driver and a mitigator of health inequities a...