Military Medicine

SDD-YOLO: A Small-Target Detection Framework for Ground-to-Air Anti-UAV Surveillance with Edge-Efficient Deployment

Detecting small unmanned aerial vehicles (UAVs) from a ground-to-air (G2A) perspective presents significant challenges, including extremely low pixel occupancy, cluttered aerial backgrounds, and strict real-time constraints. Existing YOLO-based detectors are primarily optimized for general object detection and often lack adequate feature resolution for sub-pixel targets, while introducing complexi...

From Plausibility to Verifiability: Risk-Controlled Generative OCR for Vision-Language Models

Modern vision-language models (VLMs) can act as generative OCR engines, yet open-ended decoding can expose rare but consequential failures. We identify a core deployment misalignment in generative OCR. Autoregressive decoding favors semantic plausibility, whereas OCR requires outputs that are visually grounded and geometrically verifiable. This mismatch produces severe errors, especially over-gene...

From Concept to Clinic: Real World Evidence for Autonomous AI Deployment in Primary Care Telemedicine

Systems powered by large language models are widely used for health information and advice, yet robust evidence for their safety and effectiveness in ...

ReXInTheWild: A Unified Benchmark for Medical Photograph Understanding

Everyday photographs taken with ordinary cameras are already widely used in telemedicine and other online health conversations, yet no comprehensive b...

Development of a Deep Learning Based Framework for Classification of Indian Venomous Snakes Integrated with Explainable Artificial Intelligence for primary and emergency care providers

Background Snakebite envenoming is a significant global health crisis that has been long neglected as a global health priority. It is a huge problem f...

DeepCORO-CLIP: A Multi-View Foundation Model for Comprehensive Coronary Angiography Video-Text Analysis and External Validation

Coronary angiography is the reference standard for evaluating coronary artery disease, yet visual interpretation remains variable between readers. Exi...

Safe Distributionally Robust Feature Selection under Covariate Shift

In practical machine learning, the environments encountered during the model development and deployment phases often differ, especially when a model i...

Toward Clinically Ready Foundation Models in Medical Image Analysis: Adaptation Mechanisms and Deployment Trade-offs

Foundation models (FMs) have demonstrated strong transferability across medical imaging tasks, yet their clinical utility depends critically on how pr...

Deployment-Time Reliability of Learned Robot Policies

Recent advances in learning-based robot manipulation have produced policies with remarkable capabilities. Yet, reliability at deployment remains a fun...

An FPGA Implementation of Displacement Vector Search for Intra Pattern Copy in JPEG XS

Recently, progress has been made on the Intra Pattern Copy (IPC) tool for JPEG XS, an image compression standard designed for low-latency and low-comp...

Evaluating Few-Shot Pill Recognition Under Visual Domain Shift

Adverse drug events are a significant source of preventable harm, which has led to the development of automated pill recognition systems to enhance me...

Trustworthy personalized treatment selection: causal effect-trees and calibration in perioperative medicine

Background Personalized medicine promises to tailor treatments to the individual, but it carries a hidden risk: mistaking statistical noise for action...

Care Plan Generation for Underserved Patients Using Multi-Agent Language Models: Applying Nash Game Theory to Optimize Multiple Objectives

Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must sim...

Transforming Behavioral Neuroscience Discovery with In-Context Learning and AI-Enhanced Tensor Methods

Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from data preparation to analyzing and interpreting fin...

Task-Agnostic Continual Learning for Chest Radiograph Classification

Clinical deployment of chest radiograph classifiers requires models that can be updated as new datasets become available without retraining on previou...

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

Pathology foundation models (PFMs) have enabled robust generalization in computational pathology through large-scale datasets and expansive architectu...

In Transformer We Trust? A Perspective on Transformer Architecture Failure Modes

Transformer architectures have revolutionized machine learning across a wide range of domains, from natural language processing to scientific computin...

Safety and Utility of an Agentic Large Language Model-Based Hospital Course Summarizer: A Prospective Real-World Pilot Study

Importance: High-quality discharge summaries are essential for safe care transitions but contribute substantially to clinician documentation burden an...

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Robots

Deploying learned control policies on humanoid robots is challenging: policies that appear robust in simulation can execute confidently in out-of-dist...

Development and implementation of an AI system for clinical toxicology sign-outs

Modern natural language tools have potential to improve clinical workflows, but few have been successfully deployed in practice. Here, we present the ...