Latest AI and machine learning research in military medicine for healthcare professionals.
Heart failure (HF) ranks among the foremost causes of mortality globally, exhibiting particularly high prevalence and significant impact within intensive care units (ICUs). This study sought to develop, validate, and deploy a time-dependent machine learning model aimed at predicting the one-year all-cause mortality risk in ICU patients diagnosed with HF, thereby facilitating precise prognostic ev...
The integration of machine-learning technologies into radiology practice has the potential to significantly enhance diagnostic workflows and patient care. However, the successful deployment and maintenance of medical machine-learning (MedML) systems in radiology requires robust operational frameworks. Medical machine-learning operations (MedMLOps) offer a structured approach ensuring persistent Me...
Digital diabetes management technologies (DDMTs) have emerged as promising tools for improving glycemic control in patients with type 2 diabetes melli...
PURPOSE: This study reports the implementation of a proof-of-concept, artificial intelligence (AI)-driven clinical decision support system for detecti...
We propose a sociological approach to healthcare robots that emphasises the heterogeneous ethics of mutual labour and the complex definitions of care ...
Objectives: While Large Language Models (LLMs) have been widely used to assist clinicians and support patients, no existing work has explored dialog...
The growing adoption of synthetic data in healthcare is driven by privacy concerns, limited access to real-world data, and the high cost of annotati...
In many real-world machine learning (ML) applications (e.g. detecting broken bones in x-ray images, detecting species in camera traps), in practice ...
Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion...
The advancement of AI systems for mental health support is hindered by limited access to therapeutic conversation data, particularly for trauma trea...
This paper investigates deploying semantic edge inference systems for performing a common image clarification task. In particular, each system consi...
Neural Radiance Field (NeRF) is widely known for high-fidelity novel view synthesis. However, even the state-of-the-art NeRF model, Gaussian Splatti...
The deployment of roadside LiDAR sensors plays a crucial role in the development of Cooperative Intelligent Transport Systems (C-ITS). However, the ...
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-mak...
Background: The HERMES Kiosk (Healthcare Enhanced Recommendations through Artificial Intelligence & Expertise System) is designed to provide persona...
The increasing global prevalence of mental disorders, such as depression and PTSD, requires objective and scalable diagnostic tools. Traditional cli...
The management of chronic heart failure presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of ex...
Post-Traumatic Stress Disorder (PTSD) remains underdiagnosed in clinical settings, presenting opportunities for automated detection to identify pati...
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...
The development of artificial intelligence (AI) including generative large language models (LLMs) and software like ChatGPT is likely to significantly...