Virtual patients using large language models: Scalable, contextualized simulation of clinician-patient dialog with feedback.

Background: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.

Objective: Show proof-of-concept that VPs powered by large language models (LLMs) generate authentic dialogs, accurate representations of patient preferences, and personalized feedback on clinical performance; and explore LLMs for rating dialog and feedback quality.

Peaceful dying among Canada's elderly: An analysis of the Canadian Longitudinal Study on Aging.

Introduction: Death is universal, yet relatively little is known about how Canadians experience their death. Using novel decedent interview data from the Canadian Longitudinal Study on Aging we describe the prevalence and characteristics of peace with dying among older Canadians.

Methods: We conducted a secondary analysis of decedent interview data from the Canadian Longitudinal Study on Aging.

Bioethics Principles in Machine Learning-Healthcare Application Design: Achieving Health Justice and Health Equity.

Health technologies featuring artificial intelligence (AI) are becoming more common. Some healthcare AIs are exhibiting bias towards underrepresented persons and populations. Although many computer scientists and healthcare professionals agree that eliminating or mitigating bias in healthcare AIs is needed, little information exists regarding how to operationalize bioethics principles like autonomy in product design and implementation.

Long-term Mental Health Morbidity in Adult Survivors of COVID-19 Critical Illness - A Population-based Cohort Study.

Background: Survivorship after coronavirus disease 2019 (COVID-19) critical illness may be associated with important long-term sequelae, but little is known regarding mental health outcomes.

Research Question: What is the association between COVID-19 critical illness and new post-discharge mental health diagnoses.

Study Design: AND METHODS: We conducted a population-based cohort study in Ontario, Canada (January 1, 2020-March 31, 2022).

Smoking and Risks Contributing to COVID-19 Hospitalization in Washoe County, Nevada, 2020-2021.

Objectives: To investigate the association between smoking behavior and COVID-19 hospitalization, integrating individual and regional factors such as community resilience and social determinants of health (SDOH), addressing gaps in existing research.

Design: Retrospective cohort study utilizing multilevel analytical methods to evaluate the effects of individual smoking status and regional SDOH on COVID-19 hospitalization.

Setting: Washoe County, Nevada, during the first year of the COVID-19 pandemic (March 5, 2020, to April 30, 2021).