Latest AI and machine learning research in military medicine for healthcare professionals.
Post-traumatic stress disorder (PTSD) is a complex and prevalent neuropsychiatric condition that arises in response to exposure to a traumatic event. A common diagnostic criterion for PTSD includes heightened physiological reactivity to trauma-related sensory cues, in safe or familiar environments. Understanding complex PTSD criteria requires new pre-clinical paradigms and technologies that integr...
Background: There are many challenges and opportunities in the clinical deployment of AI tools in radiology. The current study describes a radiology software platform called NeoMedSys that can enable efficient deployment and refinements of AI models. We evaluated the feasibility and effectiveness of running NeoMedSys for three months in real-world clinical settings and focused on improvement per...
The integration of large language models (LLMs) into health care offers tremendous opportunities to improve medical practice and patient care. Beside...
Patient recruitment remains a major bottleneck in clinical trials, calling for scalable and automated solutions. We present TrialMatchAI, an AI-powe...
Natural gas, as a vital component of the global energy structure, is widely utilized as an important strategic resource and essential commodity in var...
Artificial intelligence (AI) has shown effectiveness in various industries, particularly within healthcare sectors. In Nepal, there are limited insigh...
The integration of machine-learning technologies into radiology practice has the potential to significantly enhance diagnostic workflows and patient c...
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...