Military Medicine

Neutron-gamma discrimination based on STFT-DFF model and FPGA implementation.

In the field of neutron-gamma discrimination, traditional discrimination algorithms exhibit poor performance in the low-energy region, while machine learning-based discrimination algorithm face challenges such as difficulty in hardware deployment and poor real-time discrimination. To address these issues, this study proposes a machine learning-based discrimination algorithm named STFT-DFF, which i...

Patient perspectives about deployment of artificial intelligence decision support tools in a safety-net healthcare system.

OBJECTIVES: To assess patient awareness, trust, perceived benefits, and risks of artificial intelligence (AI) in clinical care within an urban safety-net health system. MATERIALS AND METHODS: We surveyed 313 patients from November 2024 to January 2025 regarding AI awareness, trust in AI-assisted decision-making, and preferences for transparency and oversight. Quantitative analyses assessed associa...

Artificial intelligence in surgical care within low-income and middle-income countries: a scoping review of development, validation, and deployment.

Artificial intelligence (AI) has the potential to expand access to high-quality surgical care in low-income and middle-income countries (LMICs), yet t...

Artificial Intelligence in Radiology: Unlocking New Dimensions of Value.

Artificial intelligence (AI) is emerging as a transformative force in radiology, offering the potential to revolutionize the field by enabling sophist...

Deployment of a machine learning-based predictive system for childhood diarrhea in Sub-Saharan Africa.

Diarrhea remains a leading cause of child mortality in Sub-Saharan Africa, necessitating advanced predictive tools for early intervention. Despite the...

[Expert consensus on the clinical application of robotic-assisted bronchoscopy].

Robotic-assisted bronchoscopy (RAB) is an emerging diagnostic and interventional technology which integrates thin-slice CT-based virtual airway recons...

DIVE: A Multi-Label Smart Contract Vulnerability Dataset.

Smart Contract (SC) vulnerabilities are programming errors or design flaws that can lead to financial loss or functional failure, making accurate dete...

Toward a multiomics framework for understanding symbiotic nitrogen fixation.

Reducing dependence on synthetic nitrogen fertilizer requires biologically grounded alternatives. Symbiotic nitrogen fixation supplies fixed nitrogen ...

Scenario-based forecasting of the global energy demand and carbon footprint of artificial intelligence.

Artificial intelligence (AI) is advancing rapidly and is emerging as a significant driver of global electricity consumption, yet its long-term energy ...

Diagnostic accuracy, fairness and clinical implementation of AI for breast cancer screening: results of multicenter retrospective and prospective technical feasibility studies.

Artificial intelligence (AI) promises to enhance breast cancer screening. Here we evaluated Google's mammography AI system (version 1.2) across two ph...

Interpretable evaluation of physiological signals for biometric identification.

Biometric systems using physiological signals have shown high identification accuracy (IA) and low Equal Error Rate (EER). However, existing research ...

Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities.

OBJECTIVES: To analyse the landscape of active US National Institutes of Health (NIH) artificial intelligence (AI) health research grants, with emphas...

Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.

Artificial intelligence (AI) is increasingly used in mental health, yet its rehabilitation-oriented applications in schizophrenia have not been system...

Enhancing adverse drug event extraction and summarization for cancer drugs through large language models.

PURPOSE: Cancer treatments such as chemotherapy, targeted therapy, and immunotherapy can effectively combat malignant cells but frequently cause serio...

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.

This perspective introduces MS360°, a conceptual hybrid care model for the management of multiple sclerosis (MS). It integrates traditional on-site as...

Prediction of Penicillin Concentration Using Time Series Forecasting and Machine Learning Techniques.

BACKGROUND: Time-series forecasting is crucial in pharmaceutical fermentation, where early detection of deviations safeguards product quality. As the ...

Reimagining Thomas Lewis's perspective: using artificial intelligence tools to predict cardiovascular risk from computed tomography.

Artificial intelligence (AI) is reshaping cardiovascular imaging, transforming it from a set of diagnostic tests into powerful tools of precision medi...

Development, application and evaluation of an artificial intelligence (AI)-based platform (SurgSmart) for the automatic assessment of the critical view of safety (CVS) in laparoscopic cholecystectomy (LC).

BACKGROUND: Laparoscopic Cholecystectomy (LC) is the standard surgical treatment for symptomatic benign gallbladder diseases. Bile Duct Injury (BDI) i...

Artificial intelligence for automated detection of joint bleeding via ultrasound in hemophilia: advancing standardization.

BACKGROUND: Musculoskeletal ultrasound (US) is a noninvasive tool for joint assessment in persons with hemophilia. Early detection of joint bleeding u...

AI Triage in Primary Care: Building Safer and More Equitable Real-World Evidence.

Artificial intelligence triage in general practice is developing rapidly within the primary care digital transformation, promising efficiency gains an...