Military Medicine

LEMUR 2: Unlocking Neural Network Diversity for AI

Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain or deployment-aware evaluation. LEMUR 2 introduces a large-scale, extensible framework unifying generative, evaluative, and deployment pipelines to unlock neural-network diversity. It comprises over 14,000 distinct architectures and more than 750,00...

Managing AI-Enabled Uncertainty in Clinical AI Deployment: Mixed-Methods Study of Governance, Workflow, and Organizational Learning in an ICU Decision Support Pilot

BackgroundHealth care organizations are increasingly required to make strategic decisions about artificial intelligence (AI) systems before their clinical value, operational consequences, governance requirements, and workforce implications are fully known. Clinical AI pilots can reduce this uncertainty only if they generate management-relevant evidence beyond retrospective model performance, inclu...

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform

This project investigates whether recent Vision-Language-Action (VLA) models can be transferred from controlled research benchmarks to a real-world ro...

ADVISE: A Machine Learning Framework for Early Recognition of a Surrogate Marker for Ventilator-Associated Pneumonia Using Routinely Collected Critical Care Data

BackgroundVentilator-associated pneumonia (VAP) is the most frequent nosocomial infection in critical care, affecting 20-36% of mechanically ventilate...

Artificial Intelligence-Enabled Cardiac Function Estimation from Phone Videos of Echocardiograms

Importance: Mobile phone-recorded echocardiogram videos are commonly used in point of care, telemedicine, and resource-limited workflows, but artifici...

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning

Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands th...

Automated Parameter Estimation for Camera Trap Density Models Using Computer Vision-Enhanced Distance Sampling

Models for estimating animal density from camera traps require four parameters informing detection: movement speed, daily activity level, staying time...

Beyond Benchmarks: Continuous Edge Inference for Fine-Grained Roadside Perception

Continuous AI inference on resource-constrained edge hardware introduces deployment effects that are largely invisible to conventional benchmark evalu...

VISTA: Scale-Aware Visual Navigation via Action History Conditioning

Vision Navigation Foundation Models (VNMs) promise end-to-end learned navigation policies capable of zero-shot deployment across diverse embodiments a...

Ride, Track, and Recover: Pilot Randomized Trial of a Wearable Digital Self-Management Intervention During a Veteran Endurance-Cycling Program

Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are di...

Multivariate Machine Learning Analysis of M-ECG-derived Heart Rate Variability in TBI Veterans, With and Without Comorbid PTSD

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) frequently co-occur in Veterans, producing overlapping symptoms and shared auton...

CollectionLoRA: Collecting 50 Effects in 1 LoRA via Multi-Teacher On-Policy Distillation

Customized image editing aims to equip pre-trained diffusion models with specific visual effects using limited paired data, typically via Low-Rank Ada...

Quantitative Evaluation of the Severity of Posttraumatic Stress Disorder through Transfer Learning from Specific Phobia Data

Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current c...

Deployment-complete benchmarking

Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports only the response it records, not necessarily the...

ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data

Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-di...

SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection

Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by sys...

Economic costing of evaluating, deploying and monitoring an artificial intelligence-based reconstruction for acceleration of rectal MRI examinations

Objectives: AI-based reconstructions can reduce MRI acquisition times and/or improve image quality. Guidelines recommend clinical evaluations and post...

Privacy-Preserving Large Language Model Deployment for Oncology Registry Abstraction: Structure-Aware Evaluation in a Real-World Clinical Setting

Background: Structuring oncology clinical notes into registry-grade variables is essential for research and care but remains labour-intensive and erro...

Language-dependent diagnostic safety of medical AI systems: a cross-lingual benchmarking and prospective clinical study

Background Patients worldwide receive healthcare in many languages, yet medical AI systems are validated almost exclusively in high-resource languages...

Real-World Validation of Machine Learning Models for HIV Treatment Adherence Prediction and Care Gap Quantification: A Multi-Country Analysis of 192,732 Clinical Records

Delayed diagnosis and poor antiretroviral therapy (ART) adherence remain primary drivers of HIV-related morbidity in low-resource settings, yet real-w...