Military Medicine

Data-driven outcome prediction and rational resource allocation in severe traumatic brain injury: a multicenter retrospective study integrating survival analysis and machine learning ensembles.

INTRODUCTION: Severe traumatic brain injury (sTBI), is a leading cause of death and disability among young and middle-aged populations worldwide. OBJECTIVE: sTBI is associated with high mortality and disability rates, and reliable risk estimation with quantified uncertainty is crucial for optimizing intensive care unit (ICU) bed allocation and nursing resource deployment. This study aimed to estab...

A Bilingual AI-Based Chatbot for Nutrition Education in a Food Is Medicine Intervention for High-Risk Pregnant Women: Design and Development Study.

BACKGROUND: Conversational agents (artificial intelligence [AI]-based chatbots) offer a novel approach to health interventions by providing personalized, adaptive interactions that improve over time based on user engagement. In nutrition education, given the wide variation in knowledge, skills, and abilities across participants, AI-based chatbots have the potential to enhance accessibility, engage...

Structural optimization principles for edge AI in motorsport telemetry.

In motorcycle motorsport, engineering decisions are constrained by mass, stiffness, fatigue life, and thermal margins. In a comparable way, deploying ...

Crack-Expansion Patterned Laser-Induced Graphene Strain Sensors for Machine Learning-Assisted Neck Posture Monitoring.

Prolonged exposure to electronic devices exacerbates neck health issues in modern populations. To address this challenge, we develop a flexible strain...

Artificial Intelligence-Powered Simulation for Telehealth Communication Training: Bridging Traditional Simulation and Artificial Intelligence.

INTRODUCTION: Traditional simulation-based communication training remains resource-intensive and difficult to scale. While artificial intelligence (AI...

Systems of Care in Cardiogenic Shock: Team-Based Management, Shock Networks, and Post Discharge Pathways.

Cardiogenic shock (CS) remains the leading cause of mortality in modern cardiac intensive care unit, most often precipitated by acute or chronically d...

AgroDualNet: a dual deep learning-based crop disease forecasting and fruit ripening detection.

Proper diagnosis of crop diseases and accurate measurement of fruit ripeness is essential in enhancing agricultural productivity, but conventional met...

Green artificial intelligence in health applications.

As the healthcare sector increasingly integrates Artificial Intelligence (AI) technologies to improve operational effectiveness, diagnosis, and therap...

Equity in the distribution of general practitioners and specialists in Iran: a health needs-adjusted analysis using the Robin Hood index (2006-2019).

BACKGROUNDS: Physicians are among the most vital healthcare resources. The equitable distribution of human resources could help policymakers to reach ...

Understanding AI risks from its characteristics and NMPA regulation perspectives.

AI is reshaping medical research and healthcare delivery, yet the translation of AI innovations into clinically approved medical devices remains limit...

Transforming clinical trials in rare genetic diseases through telemedicine.

Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties.

Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 perc...

AI-generated clinical summaries: errors and susceptibility to speech and speaker variability.

OBJECTIVES: To evaluate whether variability in patients' communication style (personality), international English-accents (human and synthetic) and sp...

Development and validation of the IVENUS artificial intelligence model for automated CEAP classification of early-stage chronic venous disease using lower limb photographs.

OBJECTIVES: Chronic venous disease (CVD) is one of the most common vascular disorders, affecting millions of people worldwide. Owing to the variabilit...

Fall Detection Based on Computer Vision: A Systematic Mapping Study.

Falls are a leading cause of injury and mortality among older adults, motivating growing interest in video-based computer vision (CV) fall detection s...

HRS scientific statement on artificial intelligence integration framework into clinical electrophysiology workflows.

Artificial intelligence (AI) and digital health technologies (DHTs) are rapidly transforming health care, offering unprecedented opportunities for enh...

Deep learning driven clustering of post-traumatic stress disorder (PTSD) profiles in student-athletes: implications for precision and stratified mental health support.

BACKGROUND: Athletes frequently experience potentially traumatic events related to sports injuries, significantly increasing their risk of developing ...

Telemedicine adoption in cardiology: Determinants and predictors identified using Bayesian Model Averaging and Machine Learning.

In this secondary analysis of a German cross-sectional survey data, we investigated key determinants and predictors of telemedicine (TM) use among hea...

Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence-Generated and Human-Produced Clinical Notes.

BACKGROUND: Ambient artificial intelligence (AI) scribes can reduce the burden of administrative documentation. Prior evaluations have been vendor spe...

LGGC-Net: a local-global graph and color attention-based lightweight CNN for skin cancer classification.

Developing clinically deployable AI systems for skin cancer classification remains challenging due to limited robustness, lack of interpretability and...