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Generative Artificial Intelligence in Anatomic Pathology.
Arch Pathol Lab Med
January 2025
the Department of Pathology, The Ohio State University, Columbus (Parwani).
Context.—: Generative artificial intelligence (AI) has emerged as a transformative force in various fields, including anatomic pathology, where it offers the potential to significantly enhance diagnostic accuracy, workflow efficiency, and research capabilities.
Objective.
Health profession students' perceptions of ChatGPT in healthcare and education: insights from a mixed-methods study.
BMC Med Educ
January 2025
Department of Nursing Sciences, Faculty of Medical and Health Sciences, The Stanley Steyer School of Health Professions, Tel Aviv University, Tel Aviv, Israel.
Objective: The aim of this study was to investigate the perceptions of health profession students regarding ChatGPT use and the potential impact of integrating ChatGPT in healthcare and education.
Background: Artificial Intelligence is increasingly utilized in medical education and clinical profession training. However, since its introduction, ChatGPT remains relatively unexplored in terms of health profession students' acceptance of its use in education and practice.
MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.
J Expo Sci Environ Epidemiol
January 2025
Department of Veterinary Physiology & Pharmacology, Texas A&M University, College Station, TX, USA.
Background: Many chemical releases are first noticed by community members, but reporting these concerns often involves considerable hurdles. Artificial Intelligence (AI)-enabled technologies, especially large language models (LLMs), can potentially reduce these barriers.
Objective: We hypothesized that AI-powered chatbots can facilitate reporting of pollution incidents through text messaging.
Transforming Physiology and Healthcare through Foundation Models.
Physiology (Bethesda)
January 2025
Department of Anesthesiology and Perioperative Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
Recent developments in artificial intelligence (AI) may significantly alter physiological research and healthcare delivery. Whereas AI applications in medicine have historically been trained for specific tasks, recent technological advances have produced models trained on more diverse datasets with much higher parameter counts. These new, "foundation" models raise the possibility that more flexible AI tools can be applied to a wider set of healthcare tasks than in the past.
View Article and Find Full Text PDFEra of Generalist Conversational Artificial Intelligence to Support Public Health Communications.
J Med Internet Res
January 2025
School of Computer Science, University of Technology Sydney, Sydney, Australia.
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication.
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