AIMC Topic: Primary Health Care

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Prevalence of Financial Considerations Documented in Primary Care Encounters as Identified by Natural Language Processing Methods.

JAMA network open
IMPORTANCE: Quantifying patient-physician cost conversations is challenging but important as out-of-pocket spending by US patients increases and patients are increasingly interested in discussing costs with their physicians.

Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model.

BMJ open
INTRODUCTION: Asthma is a long-term condition with rapid onset worsening of symptoms ('attacks') which can be unpredictable and may prove fatal. Models predicting asthma attacks require high sensitivity to minimise mortality risk, and high specificit...

Ten Ways Artificial Intelligence Will Transform Primary Care.

Journal of general internal medicine
Artificial intelligence (AI) is poised as a transformational force in healthcare. This paper presents a current environmental scan, through the eyes of primary care physicians, of the top ten ways AI will impact primary care and its key stakeholders....

Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges.

Yearbook of medical informatics
BACKGROUND: Artificial intelligence (AI) is heralded as an approach that might augment or substitute for the limited processing power of the human brain of primary health care (PHC) professionals. However, there are concerns that AI-mediated decision...

Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners' Views.

Journal of medical Internet research
BACKGROUND: The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics and related fields.

Machine Learning Enhances the Efficiency of Cognitive Screenings for Primary Care.

Journal of geriatric psychiatry and neurology
BACKGROUND: Incorporation of cognitive screening into the busy primary care will require the development of highly efficient screening tools. We report the convergence validity of a very brief, self-administered, computerized assessment protocol agai...

Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches.

Health informatics journal
Learning from patient safety incident reports is a vital part of improving healthcare. However, the volume of reports and their largely free-text nature poses a major analytic challenge. The objective of this study was to test the capability of auton...