Latest AI and machine learning research in information technology for healthcare professionals.
The field of Fake Image Detection and Localization (FIDL) is highly fragmented, encompassing four domains: deepfake detection (Deepfake), image manipulation detection and localization (IMDL), artificial intelligence-generated image detection (AIGC), and document image manipulation localization (Doc). Although individual benchmarks exist in some domains, a unified benchmark for all domains in FID...
Telecardiology has emerged as a promising approach in acute cardiac care through advancements in digital health technologies. This review explores the current evidence of telemedicine applications in acute coronary syndrome, arrhythmias, and acute heart failure. Telecardiology strategies are already implemented in clinical practice today. Examples such as pre-hospital electrocardiogram transmissio...
Clinical Document Classification (CDC) is crucial in healthcare for organizing and categorizing large volumes of medical information, leading to impro...
The proliferation of AI agents requires robust mechanisms for secure discovery. This paper introduces the Agent Name Service (ANS), a novel architec...
AI-powered LizAI XT ensures real-time and accurate mega-structure of different clinical datasets and largely inaccessible and fragmented sources, in...
Multimorbidity is increasingly prevalent as the population ages and individuals with multiple long-term conditions (MLTCs) live longer. Often each con...
This work aims to identify the Key Research Areas for building and deploying the semantic interoperability framework for the Intensive Medicine Data S...
This study analyzes 159 master's theses in Medical Informatics from the University of Porto, spanning 2006 to 2023, to identify key trends, thematic f...
The European Rolling Plan for ICT Standardization outlines activities that connect EU policies to standardization efforts in different technological d...
Mechanical ventilation is crucial for critically ill patients in ICUs, requiring accurate weaning and extubations timing for optimal outcomes. Current...
Standardizing medical terminology is critical for healthcare informatics, particularly for improving data interoperability and patient management syst...
Accurately documenting smoking status is essential for clinical decision-making and patient care. However, smoking status information is often only av...
The significance of Findable, Accessible, Interoperable, and Reusable (FAIR) data is increasing, particularly in the context of enhancing data reuse i...
The FAIR principles have been adopted across scientific disciplines to promote sustainable use of data. Ontologies play a crucial role in facilitating...
User and Entity Behaviour Analytics (UEBA) is a broad branch of data analytics that attempts to build a normal behavioural profile in order to detec...
Research projects, including those focused on cancer, rely on the manual extraction of information from clinical reports. This process is time-consu...
The integration of large language models (LLMs) into health care offers tremendous opportunities to improve medical practice and patient care. Beside...
BACKGROUND: To improve healthcare quality and empower patients, federal legislation requires nationwide interoperability of electronic health records ...
Artificial intelligence (AI) has shown effectiveness in various industries, particularly within healthcare sectors. In Nepal, there are limited insigh...
BACKGROUND: Symptoms are a core concept of nursing interest. Large-scale secondary data reuse of notes in electronic health records (EHRs) has the pot...