Latest AI and machine learning research in surveillance for healthcare professionals.
INTRODUCTION: Carrying out a systematic review (SR) of the literature entails a high workload and encompasses a variety of very different tasks. The emergence of artificial intelligence tools has brought further opportunities to improve the efficiency and reliability of SRs. SR processes can be optimised to the extent that integration and interoperability of software tools across production stages...
OBJECTIVE: The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support clinical decision-making in epilepsy. However, there currently lacks an appropriate assessment of clinical utility and study rigor of current AI/ML-driven models that are targeted toward supporting decision-making within the clinical workup in epilepsy....
PURPOSE: The COSMIN Reporting Guideline 2.0 and its Explanation & Elaboration document have been published to guide researchers in reporting studies o...
BACKGROUND: Many unhealthy habits develop in early childhood and can lead to long-term health risks, which disproportionately affect children with low...
BACKGROUND: Chaotic dynamics has been the subject of both theoretical and empirical research in epidemiology, with the most recent research strongly f...
This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and fu...
As urban areas host a large portion of the world's population, high-resolution gridded meteorological data within cities is required to answer impactf...
BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperati...
BACKGROUND: As Southeast Asian countries advance toward malaria elimination, challenges such as residual transmission reservoirs and zoonotic spill-ov...
OBJECTIVE: To develop and validate a multivariate Long Short-Term Memory (LSTM) model that integrates multi-source surveillance data for forecasting i...
BACKGROUND: Nontyphoidal Salmonella enterica (NTS) is a major public‑health threat in the United States of America (U.S.). Evaluating associations bet...
BACKGROUND: Humanitarian settings are highly vulnerable to infectious disease outbreaks because displacement, crowding, disruption of health services,...
BACKGROUND: While generative artificial intelligence (AI) is rapidly proliferating in healthcare research and clinical settings, there is a lack of ac...
Echinococcosis poses a major public-health challenge and substantial socioeconomic burdens in pastoral regions. Yet the spatial transmission risks in ...
Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 has substantially advanced the standardization of prostate MRI acquisition, interpret...
OBJECTIVES: To estimate patient-level diagnostic accuracy of deep learning (DL) for MRI-based detection of clinically significant prostate cancer (csP...
BACKGROUND: Depression is a major public health concern, with Tennessee ranking among the U.S. states with the highest prevalence. Despite its burden,...
BACKGROUND: Longitudinal serum uric acid (SUA) transition patterns and their clinical, genetic, and dietary determinants remain poorly characterized. ...
BACKGROUND: Dental pulp calcifications, including pulp stones and diffuse calcific changes, can complicate endodontic access, canal negotiation, and t...
BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...