Military Medicine

Explainable and clinically audited hybrid self-supervised framework for multi-class DFU classification and mobile deployment.

Accurate and explainable classification of diabetic foot ulcers (DFUs) is vital for early intervention and patient management. This paper presents a Clinically Audited Hybrid Self-Supervised Framework integrating domain-adaptive SimCLR pretraining, a U-Net-based refiner, and an EfficientNet-B0 classifier for four-class DFU diagnosis (Normal, Abnormal, Ischemic, Infected) by fusing two DFU datasets...

Shifting from black box decisions to informed decision-making in using artificial intelligence to analyze prostate MRI.

Prostate magnetic resonance imaging (MRI) is central to the detection and localization of clinically significant prostate cancers. However, its interpretation is time-consuming and variable. Artificial intelligence (AI) tools for prostate MRI are rapidly emerging, with their performance approaching that of expert readers in select settings, although robust external validation in unselected real-wo...

Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.

BACKGROUND: Prolonged postoperative intensive care unit (ICU) length of stay (LOS) after coronary artery bypass grafting (CABG) drives resource use ye...

Retinal vascular parameters as AI-driven biomarkers for pulse wave velocity assessment: a telemedicine strategy for cardiovascular risk assessment.

BACKGROUND: Pulse wave velocity (PWV), known as the gold standard for evaluating arterial stiffness, is limited by device dependence. This study aims ...

Metaheuristic-driven machine learning study for early detection and classification of Parkinson's disease using feature prioritization with pelican optimization algorithm.

Parkinson disease (PD) is a degenerative disorder of the brain and afflicts approximately 6 in 10 people aged 50 years or older. PD patients have moto...

AI-assisted Software Development in Digital Dentistry: A Technical Innovation Report with Three Open-Source Applications.

OBJECTIVES: To present a feasible workflow for artificial intelligence (AI)-assisted software engineering in dentistry as a technical innovation repor...

Image segmentation of track bolts based on improved YOLO model.

Railway track bolt detection is critical for high-speed railway safety maintenance, yet existing methods often suffer from high false detection rates ...

State-of-the-art TinyML approaches for colorectal cancer detection: Current advances, challenges, and future directions.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with diagnostic disparities, particularly pronounced in resourc...

Translational applications of artificial intelligence and machine learning for mosquito-borne disease control in low- and middle-income countries.

OBJECTIVES: To synthesize evidence on the application of artificial intelligence (AI) and machine learning (ML) for mosquito-borne disease (MBD) contr...

Empowering digital health management with on-device large language models for glucose prediction: a model development and validation study.

BACKGROUND: Long-term management of chronic diseases such as diabetes is increasingly based on wearable technologies, particularly continuous glucose ...

Value operating system: a practical framework to measure outcomes-per-cost at the episode level.

OBJECTIVE: To specify a value operating system (VOS) and its executable metric-the Value Index (VI)-that expresses risk-adjusted outcomes-per-episode-...

Model architecture dominates nutritional estimation accuracy in vision-language systems.

Vision-language models (VLMs) enable automated dietary assessment from food photographs, yet optimal deployment strategies remain unestablished. We ev...

A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE).

BACKGROUND: The prevalence of post-traumatic stress disorder (PTSD) among South Korean firefighters is likely to be under-reported because of stigma a...

Impact of Exposure Parameters on Deep Learning Models in Chest Radiography and Implications for Deployment.

Purpose To investigate whether deep learning models trained on chest radiographs (CXRs) rely on radiographic exposure parameters as shortcut features ...

Artificial Intelligence and Algorithmic Bias in Burn Care: A Literature Review of Ethical Challenges.

Artificial intelligence (AI) is increasingly integrated into burn care for triage, burn-depth assessment, prognostic scoring, pain management, and tel...

[Beyond the bladder-a specialty rediscovering itself: Outpatient. Networked. Digital].

BACKGROUND: Urology is undergoing a fundamental transformation characterized by increasing outpatient care, digitalization, and cross-sectoral network...

Vision-Based Artificial Intelligence Technologies for Epilepsy Monitoring: Scoping Review and Taxonomy Development Study.

BACKGROUND: Artificial intelligence (AI) technologies for vision-based epilepsy monitoring are advancing rapidly in health care. Despite growing resea...

Enhancing Physician Resilience to Generative AI: Multilevel Framework for Shared Authority, Verification, and Skill Preservation.

As generative artificial intelligence (AI), particularly large language model-based tools, is increasingly integrated into diagnosis, triage, decision...

Explainable and Interpretable AI for Voice and Speech Analysis in Clinical Care: Systematic Review.

BACKGROUND: Driven by recent advances in artificial intelligence (AI), particularly in medicine, audio-based voice and speech biomarkers are increasin...

[Digital transformation in multiple sclerosis: Advances in diagnostics, monitoring and patient-centred care].

Digital transformation is fundamentally changing the diagnosis, monitoring and treatment of multiple sclerosis. The integration of multimodal data fro...