Latest AI and machine learning research in domestic violence for healthcare professionals.
BACKGROUND: Matching the necessary resources and facilities to attend to the needs of trauma patients is traditionally performed by clinicians using criteria-directed triage protocols. In the present study, it was hypothesized that an artificial intelligence (AI) model should be able to predict the need for major surgery based on data available at the scene.
As Artificial intelligence (AI) has been increasingly integrated into the medical field, the role of humans may become vague. While numerous studies highlight AI's potential, how humans and AI collaborate to maximize the combined clinical benefits remains unexplored. In this work, we analyze 270 screening scenarios from a health-economic perspective in a national diabetic retinopathy screening p...
Parkinson's disease (PD) is a prevalent neurodegenerative disorder globally. The eye's retina is an extension of the brain and has great potential i...
Road fatalities pose significant public safety and health challenges worldwide, with pedestrians being particularly vulnerable in vehicle-pedestrian...
Despite decades of advancements in automated ligand screening, large-scale drug discovery remains resource-intensive and requires post-processing hi...
This paper introduces AIJIM, the Artificial Intelligence Journalism Integration Model -- a novel framework for integrating real-time AI into environ...
Foundation models - models trained on broad data that can be adapted to a wide range of downstream tasks - can pose significant risks, ranging from ...
Current practices for reporting the level of differential privacy (DP) guarantees for machine learning (ML) algorithms provide an incomplete and pot...
As facial recognition is increasingly adopted for government and commercial services, its potential misuse has raised serious concerns about privacy...
Although diffusion-based techniques have shown remarkable success in image generation and editing tasks, their abuse can lead to severe negative soc...
Image-based sexual abuse (IBSA) refers to the nonconsensual creating, taking, or sharing of intimate images, including threats to share intimate ima...
Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lac...
Scoring functions (SFs) of molecular docking is a vital component of structure-based virtual screening (SBVS). Traditional SFs yield their inherent sh...
Predicting clinical outcomes from preclinical data is essential for identifying safe and effective drug combinations. Current models rely on structu...
Children with neurodevelopmental disorders require timely intervention to improve long-term outcomes, yet early screening remains inaccessible in ma...
Online abuse, a persistent aspect of social platform interactions, impacts user well-being and exposes flaws in platform designs that include insuff...
Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally detected, and bron...
Background Multimodal generative artificial intelligence (AI) technologies can produce preliminary radiology reports, and validation with reader studi...
Recent advancements in AI and medical imaging offer transformative potential in emergency head CT interpretation for reducing assessment times and i...
Linear $L_1$-regularized models have remained one of the simplest and most effective tools in data science. Over the past decade, screening rules ha...