Latest AI and machine learning research in information technology for healthcare professionals.
Language is not neutral; it frames understanding, structures power, and shapes governance. This paper argues that misnomers like cybersecurity and artificial intelligence (AI) are more than semantic quirks; they carry significant governance risks by obscuring human agency, inflating expectations, and distorting accountability. Drawing on lessons from cybersecurity's linguistic pitfalls, such as ...
The recent proliferation of blockchain-based decentralized applications (DApp) has catalyzed transformative advancements in distributed systems, with extensive deployments observed across financial, entertainment, media, and cybersecurity domains. These trustless architectures, characterized by their decentralized nature and elimination of third-party intermediaries, have garnered substantial in...
The rapid accumulation of Electronic Health Records (EHRs) has transformed healthcare by providing valuable data that enhance clinical predictions a...
WebShell attacks, in which malicious scripts are injected into web servers, are a major cybersecurity threat. Traditional machine learning and deep ...
The purpose of research: Detection of cybersecurity incidents and analysis of decision support and assessment of the effectiveness of measures to co...
Foundation models (FMs) trained on electronic health records (EHRs) have shown strong performance on a range of clinical prediction tasks. However, ...
Neural Radiance Field (NeRF) is widely known for high-fidelity novel view synthesis. However, even the state-of-the-art NeRF model, Gaussian Splatti...
Electronic health record (EHR) foundation models have been an area ripe for exploration with their improved performance in various medical tasks. De...
The temporal complexity of electronic health record (EHR) data presents significant challenges for predicting clinical outcomes using machine learni...
Blood cultures are often over ordered without clear justification, straining healthcare resources and contributing to inappropriate antibiotic use p...
Adverse Drug Events (ADEs), harmful medication effects, pose significant healthcare challenges, impacting patient safety and costs. This study evalu...
Background: The HERMES Kiosk (Healthcare Enhanced Recommendations through Artificial Intelligence & Expertise System) is designed to provide persona...
The management of chronic heart failure presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of ex...
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...
Hospital-acquired infections (HAIs) significantly burden global healthcare systems, exacerbated by antibiotic-resistant bacteria. Traditional infectio...
INTRODUCTION: Optimal use of HIV testing resources accelerates progress towards ending HIV as a global threat. In Kenya, current testing practices yie...
Objective: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performa...
Reasoning before action and imagining potential outcomes (i.e., world models) are essential for embodied agents operating in complex open-world envi...
Electronic Health Records (EHR) have become a valuable resource for a wide range of predictive tasks in healthcare. However, existing approaches hav...
High hospital readmission rates are associated with significant costs and health risks for patients. Therefore, it is critical to develop predictive...