Latest AI and machine learning research in domestic violence for healthcare professionals.
Integrity of scientific data is critical in biomedical research, where images often serve as primary evidence for experimental observations and conclusions. Advances in image-editing technologies and generative artificial intelligence (AI) have increased the accessibility and realism of visual manipulation, making detection through manual review increasingly challenging. To empower our laboratory ...
Child Sexual Abuse Imagery (CSAI) classification systems are needed solutions for lessening the psychological impacts often felt by law enforcement agents responsible for evaluating these materials and for efficient removal of these materials from the web. However, due to the nature of the task, researching and developing such systems is not a trivial endeavor. The images are highly sensitive, and...
Autonomous network-security response systems promise to reduce Security Operations Centre (SOC) reaction latency, but reward-only multi-agent reinforc...
Background The European Association for the Study of the Liver (ESAL) - Steatotic Liver Disease (SLD) screening algorithm involves two steps; initial ...
HLA-E presented cancer peptides can be promising cancer therapy targets, as HLA-E is minimally polymorphic and widely expressed across human populatio...
This study aims to assess women's perceptions of artificial intelligence (AI) used in breast cancer screening in France by examining their knowledge o...
Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical applicat...
Raw numerical datasets remain less systematically examined in integrity screening than images, plagiarism, or summary-statistic inconsistencies. We de...
Veterinary pharmacovigilance systems are essential for monitoring adverse drug events (ADEs), yet existing approaches often fail to capture region-spe...
Background: Colon capsule endoscopy (CCE) has been proposed as a non-invasive alternative to colonoscopy for colorectal cancer (CRC) screening, offeri...
Background: Hospital incident risk scoring has long relied on two- or three-dimensional frameworks (Severity Assessment Codes or Risk Priority Numbers...
Objectives: The aim of mammographic screening is the early detection of invasive cancers. In the era of artificial intelligence (AI), this tool may im...
In an era dominated by big data and machine learning, establishing valuable data collaboration has never been more critical. However, such collaborati...
Modern deep learning offers powerful tools for automated retinal screening, but it remains unclear how different visual model families compare in real...
Purpose: Psychological distress is highly prevalent in glaucoma and is associated with worse adherence, reduced quality of life, and faster disease pr...
Background Community-wide active case-finding (ACF) is being increasingly implemented as a tuberculosis (TB) elimination intervention. However, conven...
Background: Large-scale estimates of animal-to-human drug translation and the study characteristics associated with successful translation remain limi...
Rheumatic heart disease (RHD) remains a major public health concern across low- and middle-income countries in the Global South. Early detection throu...
Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima...
Objective: How structured clinical features and cluster-semantic embeddings interact under self-distillation in EHR prediction models is unknown. Exis...