AI Medical Compendium Topic

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

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Large Language Models in Biochemistry Education: Comparative Evaluation of Performance.

JMIR medical education
BACKGROUND: Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have started a new era of innovation across various fields, with medicine at the forefront of this technological revolution. Many studies i...

Explaining disparities in robot applications among nations and regions: A cross-level lens of cultural tightness-looseness.

PloS one
In this study, we aim to explain the large disparities among countries and regions on industrial robot application in terms of robot density and robot growth. Based on the premise that people in all cultures have the same potential for innovation, we...

Large-Scale Deep Learning-Enabled Infodemiological Analysis of Substance Use Patterns on Social Media: Insights From the COVID-19 Pandemic.

JMIR infodemiology
BACKGROUND: The COVID-19 pandemic intensified the challenges associated with mental health and substance use (SU), with societal and economic upheavals leading to heightened stress and increased reliance on drugs as a coping mechanism. Centers for Di...

Mental health practitioners' perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study.

BMC health services research
BACKGROUND: As mental health disorders continue to surge, exceeding the capacity of available therapeutic resources, the emergence of technologies enabled by artificial intelligence (AI) offers promising solutions for supporting and delivering patien...

Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study.

JMIR medical education
BACKGROUND: As artificial intelligence and machine learning become increasingly influential in clinical practice, it is critical for future physicians to understand how such novel technologies will impact the delivery of patient care.

Identifying the key predictors of positive self-perceptions of aging using machine learning.

Social science & medicine (1982)
This study aimed to identify key predictors of self-perceptions of aging (SPA) among older adults by examining a comprehensive set of potential predictors across physical, psychological, social, and demographic domains. Data from over 4000 American a...

AI in health care: closing the revenue cycle gap.

The American journal of managed care
This commentary explores the current state, challenges, and potential of artificial intelligence (AI) in health care revenue cycle management, emphasizing collaboration, data standardization, and targeted implementation to enhance adoption.

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...

Greenspace and depression incidence in the US-based nationwide Nurses' Health Study II: A deep learning analysis of street-view imagery.

Environment international
BACKGROUND: Greenspace exposure is associated with lower depression risk. However, most studies have measured greenspace exposure using satellite-based vegetation indices, leading to potential exposure misclassification and limited policy relevance. ...