AI Medical Compendium Topic

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Improving explainability of post-separation suicide attempt prediction models for transitioning service members: insights from the Army Study to Assess Risk and Resilience in Servicemembers - Longitudinal Study.

Translational psychiatry
Risk of U.S. Army soldier suicide-related behaviors increases substantially after separation from service. As universal prevention programs have been unable to resolve this problem, a previously reported machine learning model was developed using pre...

A deep learning analysis for dual healthcare system users and risk of opioid use disorder.

Scientific reports
The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines. Veterans who receive care from both VA and non-VA providers-known as dual-system users-have an inc...

Leveraging machine learning to uncover multi-pathogen infection dynamics across co-distributed frog families.

PeerJ
BACKGROUND: Amphibians are experiencing substantial declines attributed to emerging pathogens. Efforts to understand what drives patterns of pathogen prevalence and differential responses among species are challenging because numerous factors related...

Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study.

PloS one
OBJECTIVES: This study aims to evaluate the performance of the latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions.

Machine Learning-Based Real-Time Survival Prediction for Gastric Neuroendocrine Carcinoma.

Annals of surgical oncology
BACKGROUND: This study aimed to develop a dynamic survival prediction model utilizing conditional survival (CS) analysis and machine learning techniques for gastric neuroendocrine carcinomas (GNECs).

XIS-PM: A daily spatiotemporal machine-learning model for PM in the contiguous United States.

Environmental research
Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a ...

Evaluation of an AI-Based Voice Biomarker Tool to Detect Signals Consistent With Moderate to Severe Depression.

Annals of family medicine
PURPOSE: Mental health screening is recommended by the US Preventive Services Task Force for all patients in areas where treatment options are available. Still, it is estimated that only 4% of primary care patients are screened for depression. The go...

A machine learning approach to estimate domestic use of public and private water sources in the United States.

Water research
In the United States, people obtain water for household use from one of two sources. Public water systems, which are subject to rules and regulations under the Safe Drinking Water Act, or private sources such as domestic wells, which are not subject ...

Predictors of treatment attrition among individuals in substance use disorder treatment: A machine learning approach.

Addictive behaviors
BACKGROUND: Early treatment discontinuation in substance use disorder treatment settings is common and often difficult to predict. We leveraged a machine learning approach (i.e., random forest) to identify individuals at risk for treatment attrition,...