AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed.

Journal of environmental management
Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Mac...

Lack of Data Access, but Not Availability, Hinders AI Training for High-Risk Conditions in Ontario.

Studies in health technology and informatics
Advanced disease prediction is an important step toward achieving a proactive healthcare system. New technologies such as artificial intelligence are very promising in their ability to predict the onset of future disease much earlier than has been po...

Machine Learning to Allocate Palliative Care Consultations During Cancer Treatment.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: For patients with advanced cancer, early consultations with palliative care (PC) specialists reduce costs, improve quality of life, and prolong survival. However, capacity limitations prevent all patients from receiving PC shortly after diag...

Socio-demographic predictors of not having private dental insurance coverage: machine-learning algorithms may help identify the disadvantaged.

BMC public health
BACKGROUND: For accessing dental care in Canada, approximately 62% of the population has employment-based insurance, 6% have some publicly funded coverage, and 32% have to pay out-of pocket. Those with no insurance or public coverage find dental care...

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.

Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

American heart journal
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...

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 ...

Prediction of preterm birth in multiparous women using logistic regression and machine learning approaches.

Scientific reports
To predict preterm birth (PTB) in multiparous women, comparing machine learning approaches with traditional logistic regression. A population-based cohort study was conducted using data from the Ontario Better Outcomes Registry and Network (BORN). Th...

Identifying Psychosocial and Ecological Determinants of Enthusiasm In Youth: Integrative Cross-Sectional Analysis Using Machine Learning.

JMIR public health and surveillance
BACKGROUND: Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational succes...

Regulating professional ethics in a context of technological change.

BMC medical ethics
BACKGROUND: Technological change is impacting the work of health professionals, especially with recent developments in artificial intelligence. Research has raised many ethical considerations respecting clinical applications of artificial intelligenc...