Military Medicine

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), particularly large language models, offers promising solutions for health care education, no blueprint exists for integrating AI-powered simulation training within operational quality improvement (QI) frameworks. This paper presents a 5-phase meth...

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 decompensated heart failure or acute myocardial infarction. Despite technologic advances, timely recognition and effective management of CS remain challenging and demand a coordinated, patient-centered and multidisciplinary approach. In this review, w...

CADP: Connection-Aware DenseNet Pruning for lightweight plant disease classification.

Plant diseases threaten global agriculture, and deep learning-based disease recognition has become crucial for addressing this challenge. While DenseN...

Clinical AI is Not (Yet) Trustworthy-But It Could Be.

The growing emphasis on trustworthy artificial intelligence (AI) in health care reflects a shift away from models optimized for predictive performance...

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...

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 ...

Machine Learning Prediction of Hospital Stay in Pediatric Typhoid Intestinal Perforation: Pilot Study.

INTRODUCTION: Typhoid intestinal perforation (TIP) remains a significant cause of pediatric morbidity in resource-limited settings, with prolonged hos...

MethylSense: high accuracy machine learning-based diagnostics for Aspergillus fumigatus infection in chickens using host cell-free DNA methylation and Nanopore sequencing.

Avian aspergillosis, caused by Aspergillus fumigatus (Af), lacks sensitive antemortem diagnostics. Existing microbial cell-free DNA (cfDNA) tests are ...

Development and Deployment of an Explainable Machine Learning Model for Preoperative Prediction of Thigh Liposuction Volume in Female Patients.

BACKGROUND: Accurate preoperative estimation of liposuction volume is essential for achieving optimal aesthetic outcomes and minimizing surgical compl...

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...

Multimodal Depression Detection Through Conversational Interactions with an Emotion-Aware Social Robot: Pilot Study.

BACKGROUND: Depression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnosti...

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...

Omission and hallucination prevalence of clinical guidelines in diagnostic large language model outputs.

OBJECTIVE: Meaningful assessments of how large language models (LLMs) incorporate clinical guidelines require large-scale testing over many queries. H...

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...

PlantaNet and PlantaNetLite: Efficient and explainable multi-crop plant disease classification via transformer benchmarking and custom lightweight CNNs.

Plant disease diagnosis based on visual symptoms is crucial for preventing yield loss; however, deployment in practical settings remains challenging d...

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...

Amphibious passive adaptation in untethered soft robots.

Mobile robots are increasingly deployed in diverse settings, ranging from logistic and household applications to ecological monitoring and operation i...

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...

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 ...