Latest AI and machine learning research in military medicine for healthcare professionals.
In this secondary analysis of a German cross-sectional survey data, we investigated key determinants and predictors of telemedicine (TM) use among healthcare professionals (HCPs) treating cardiology patients. We applied Bayesian Model Averaging (BMA) for explanatory analysis and Machine Learning (ML) for predictive modeling. BMA identified TM determinants after excluding collinear variables and se...
Human action recognition has become increasingly important for applications in security surveillance, healthcare monitoring, and smart environments. However, existing deep learning models typically require substantial computational resources, making deployment on resource-constrained edge devices challenging. To address this limitation, we propose TinyAct, a lightweight framework for real-time hum...
Breast cancer prognosis and treatment outcomes are shaped by intricate interplay between tumor biology, systemic comorbidities, and patient-reported f...
Carbon benefit assessment of energy crop deployment (ECD) is crucial for achieving climate commitments, yet the current lack of a comprehensive evalua...
BACKGROUND: Ambient artificial intelligence (AI) scribes can reduce the burden of administrative documentation. Prior evaluations have been vendor spe...
Developing clinically deployable AI systems for skin cancer classification remains challenging due to limited robustness, lack of interpretability and...
BACKGROUND AND OBJECTIVE: Radiomics-based machine learning models hold promise for clinical decision support, yet their deployment may be limited by t...
BACKGROUND: Conflict zones severely disrupt healthcare access, with millions affected by armed conflicts. The lack of standardized medical guidance ex...
BACKGROUND: The Pediatric Assessment Triangle (PAT) is a rapid visual assessment framework designed to support early identification of critically ill ...
PURPOSE: Exchange maneuvers during intracranial angioplasty and stent deployment can cause unintended distal tip motion, potentially leading to vessel...
Diabetic foot ulcers, resulting from neuropathic and/or vascular complications in patients with diabetes mellitus, pose a major global health challeng...
In the past decade there has been an increasing attention towards the field of musical haptics for the listener, which concerns the creation and evalu...
Accurate and efficient grain quality assessment is critical for making informed decisions throughout the grain value chain. Early detection of disease...
BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...
BACKGROUND: AI-based burn depth assessment is rapidly emerging, yet evidence for diagnostic accuracy, generalizability, and deployment readiness remai...
The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...
UNLABELLED: Electronic Health Records (EHRs) provide rich opportunities for developing risk prediction tools to support clinical decision-making, yet ...
BACKGROUND: Visual identification and verification of medications during dispensing and administration are prone to human error, particularly in high-...
Artificial intelligence (AI) is rapidly reshaping clinical oncology, as cancer care increasingly relies on integrating heterogeneous data streams span...
BACKGROUND: Passive smartphone sensing shows promise for suicide prevention, but behavioral metadata (GPS, screen time, and accelerometry) often lacks...