Latest AI and machine learning research in military medicine for healthcare professionals.
Injuries in elite sports disrupt team performance, shorten careers, and incur significant financial costs, highlighting the critical need for accurate predictions to inform optimal decisions that effectively prevent injuries. Existing approaches to injury prediction fail to account for cumulative risk, overlook injury severity, lack reliable probability calibration, and omit statistically guided d...
Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations compared to non-Hispanic whites. While artificial intelligence (AI) shows promise in healthcare delivery, concerns exist that AI-based interventions may disadvantage non-English-speaking populations due to biases in development and deployment. To evaluate the effectiveness of a bilingual AI ...
Despite increasingly widespread use of artificial intelligence-driven ambient scribes in medicine, the extent to which they may impact clinician pract...
Artificial intelligence (AI) has the potential to revolutionize clinical decision-making and significantly improve patient outcomes in outpatient prim...
The open-source release of DeepSeek-R1, a high-performing large language model (LLM), enables local deployment in Chinese hospitals. However, empirica...
Large language models (LLMs) offer promise for enhancing clinical care by automating documentation, supporting decision-making, and improving communic...
This study explores Artificial Intelligence (AI)’s transformative role in diabetes care and monitoring, focusing on innovations that optimize patient ...
This review explores the transformative role of artificial intelligence (AI) in the early detection and prognosis prediction of diabetic retinopathy (...
Artificial intelligence (AI) has impacted healthcare at urban and academic medical centers globally. The current focus on AI deployments in urban area...
Artificial intelligence (AI) is increasingly used to support clinical decision-making, particularly in primary care triage. However, few studies have ...
We present a real-world deployment of a large language model-powered colonoscopy recall pipeline that structured over 100,000 patient records during a...
The ongoing war in Ukraine has exposed young adults to sustained psychological stress, elevating their risk of developing post-traumatic stress disord...
One of the most difficult challenges in pediatric telemedicine is to accurately discriminate between the ‘sick’ and ‘not sick’ child, especially in re...
Most evaluations of artificial intelligence (AI) in medicine rely on static, multiple-choice benchmarks that fail to capture the dynamic, sequential n...
Sepsis remains a leading cause of mortality in intensive care units (ICUs) worldwide, underscoring the urgent need for early detection to improve pati...
Unplanned hospital admissions impose substantial strain on healthcare systems, yet predictive models for these events remain underexplored in practice...
GAI tools are increasingly used informally for health, yet evidence from low- and middle-income countries (LMICs) is limited. This study generates ear...
Standardized assessment of clinical quality measures from electronic health records (EHRs) is challenging because information is fragmented across str...
Hospital readmissions represent a persistent challenge for healthcare systems, often stemming from inadequate post-discharge monitoring. This study pr...
Artificial intelligence (AI) applied to routine electrocardiograms (ECGs) offers promise for screening of structural heart disease (SHD), yet broad cl...