Military Medicine

Research priorities for data science and artificial intelligence in global health: an international consensus exercise.

Applications of data science and artificial intelligence (AI) in global health are expanding, yet research remains fragmented and often misaligned with the needs of low-income and middle-income countries (LMICs). To address this misalignment, we conducted a global research priority-setting exercise using the Child Health and Nutrition Research Initiative (CHNRI) method. 155 research ideas were sco...

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain-Machine Interface.

Episodic memory integrates what, where, and when of experience into a coherent autobiographical narrative. Decades of research have identified hippocampal place, time, and concept cells as neural correlates of these components. Yet a major challenge remains: real-life memory encoding occurs in high-dimensional, naturalistic settings, where multimodal sensory, emotional, and cognitive processes int...

Changes in personality functioning following psychotherapy: Utilizing machine learning to identify predictors in a psychodynamic psychotherapy sample.

INTRODUCTION: Although personality functioning has a long psychodynamic tradition and has received renewed interest in psychotherapy research with the...

A joint CNN-Bi-LSTM-transformer architecture with SHAP explanations for multi-label arrhythmia detection from 12-lead ECGs.

Interpretable, automated Artificial Intelligence (AI) solutions are essential for accurate 12-lead electrocardiogram (ECG) arrhythmia classification b...

The Utility of Automated, Data-Driven Clinical Support in Telemedicine for Critical Illness: A Survey-Based Study.

A growing number of data-driven clinical decision support (CDS) tools are incorporated into tele-critical care, but the clinician perceptions of their...

Effectiveness of transcranial direct current stimulation (tDCS) on attention and memory biases in individuals with post-traumatic stress disorder (PTSD): a randomized, single-blind, parallel-group study.

Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...

Reconfigurable Multiscroll Memristive Neural Network With Application to Telemedicine Privacy Protection.

Constructing memristive neural networks (MNNs) with multiscroll chaotic attractors helps advance both theoretical and applied research on neural netwo...

Financial impact of deep learning reconstruction in magnetic resonance imaging: experiences after widespread deployment.

PURPOSE: To evaluate the impact of deep learning reconstruction (DLR) on MRI productivity at a tertiary care academic hospital, and to validate a prev...

Bias-Mitigated AI as a Foundation for Resilient and Effective Health Systems.

Artificial intelligence (AI) is rapidly reshaping the landscape of health care, from clinical diagnostics and disease surveillance to the prediction o...

Could sleep engineering be used to combat PTSD and depression?

Sleep engineering could be developed to provide a drug-free, non-invasive avenue to treat depression and post-traumatic stress disorder. Such an inter...

Development and proof-of-concept of a treatment target recommendation algorithm in the context of cognitive processing therapy.

Background: Cognitive Processing Therapy (CPT) is an effective, widely supported treatment for PTSD, but patient response varies considerably. Optimal...

A hybrid CNN-spectral architecture for non-contact respiratory rate estimation using multi-region optical-flow analysis.

Respiratory rate (RR) is a key indicator for assessing health conditions, yet noncontact measurement remains challenging due to motion artifacts, ligh...

Screening for Clinically Significant Nephrolithiasis Based on Simple Health Checkup Clinical and Urine Parameters in General Populations: Multicenter Machine Learning Study.

BACKGROUND: Nephrolithiasis affects approximately 15% of the population and often remains undetected in asymptomatic individuals. Current diagnostic a...

Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review.

BACKGROUND: The exponential growth of medical data and advancements in artificial intelligence (AI) have accelerated the development of data-driven he...

Artificial Intelligence in African Cardiovascular Care: Opportunities, Challenges, and Pathways to Improved Outcomes.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality in Africa, accounting for over 1 million deaths annually. As CVD preva...

Sustainable Ophthalmology Applications: From the Perspective of Strabismus and Pediatric Ophthalmology.

Ophthalmology significantly contributes to the healthcare sector's carbon footprint. Despite recent increases in sustainability research in ophthalmol...

Adoption of AI-Based Scribes in Telemedicine: Provider Attitudes and Insights.

BACKGROUND: Technological advancements and legislation have led to the widespread use of electronic health records (EHRs) in the 21st century. Along w...

Artificial intelligence translation in healthcare: an urgent call for evidence-informed policy frameworks.

The deployment of artificial intelligence (AI) translation tools in healthcare is accelerating rapidly, yet regulatory frameworks lag dangerously behi...

Prediction of athlete performance based on a gradient regression model.

Accurate prediction of athlete performance is a challenges issue of significance in sports science and analytics and has application in training desig...

Direct Integration of Ionic Liquid Gel Sensors onto Microfibrous Face Mask Substrates for Wearable Respiratory Health Monitoring.

Mask-integrated respiratory sensors are promising for noninvasive monitoring of respiratory health outside of clinical settings, for example, to suppo...