Domestic Violence

Economic evaluation of artificial intelligence for cancer detection in the UK breast screening programme.

BACKGROUND: Artificial intelligence (AI) offers a potential solution to radiologist shortages in breast cancer screening while maintaining diagnostic accuracy. Retrospective studies suggest AI performs comparably to human readers in detecting cancers, but no economic evaluations have yet used prospective trial data. METHODS: We developed a de novo discrete-event simulation model to estimate the co...

Artificial intelligence on chest X-ray for tuberculosis screening in Tanzania: a multicentre evaluation.

Tanzania has adopted artificial intelligence (AI)-assisted chest X-ray screening for tuberculosis (TB), including the use of CAD4TB version 6, which is registered by the Tanzania Medicines and Medical Devices Authority (TMDA). While GeneXpert, practical reference standard used in routine practice, remains the primary bacteriological confirmatory test in routine practice, there is currently no esta...

Noninvasive Screening for High-Risk Esophageal Varices in Cirrhosis: Current and Emerging Methods.

The primary goal of variceal screening in patients with cirrhosis is to identify high-risk esophageal varices (HREV) and implement preventative measur...

Impact of Artificial Intelligence-Assisted Endoscopy on Screening for Upper Gastrointestinal Cancer in a Large-Scale Health Screening Facility.

OBJECTIVES: Artificial intelligence (AI)-assisted endoscopy has been developed for the early detection of upper gastrointestinal cancer; however, its ...

Artificial Intelligence-Based Analysis of Laparoscopic Imaging for Intraoperative Surgical Decision Support.

Across surgical specialties, minimally invasive (laparoscopic) surgery has become a standard technique, as it is associated with less trauma, reduced ...

Interactive active learning for literature screening: finetuning GPT with DeepSeek reasoning for cross-domain generalization.

OBJECTIVE: Automated literature screening in biomedical research is often hindered by domain shifts and scarcity of labeled data, which limit model ac...

Identifying Food Packaging Migrants: Current Analytical Capabilities, Challenges, and Future Prospects.

The migration of intentionally and non-intentionally added substances (IAS/NIAS) from food packaging into foodstuffs presents a significant challenge ...

AI-Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review.

Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions ...

Automated approaches to identifying clinical trials based on title and abstract in the field of physiotherapy: a comparative analysis.

OBJECTIVE: To compare accuracy, precision, recall, F1 and time spent using commercial tools to identify physiotherapy trials based on title and abstra...

Artificial intelligence-driven early screening and diagnosis of pancreatic cancer: technical innovations, clinical applications, and precision medicine strategies.

BACKGROUND: Pancreatic cancer is characterized by prolonged subclinical progression, molecular heterogeneity, and late clinical presentation, resultin...

An integrated in silico and multi-omics workflow identifies novel microbiota-derived umami peptides and elucidates T1R1/T1R3 binding mechanisms.

Microbiota-derived umami peptides show strong potential for industrial applications, yet efficient high-throughput screening remains challenging. To a...

Revolutionizing lung cancer screening: the rise of artificial intelligence integrating circulating tumor markers.

Lung cancer persists as the predominant oncological cause of mortality globally, underscoring an imperative public health issue that demands effective...

Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.

BACKGROUND: Central line-associated blood stream infection (CLABSI) surveillance is mandated and publicly reported in United States hospitals but requ...

A review of machine learning in toxicology: current practices and reporting gaps.

In recent years, machine learning and artificial intelligence approaches have been increasingly applied in the context of toxicological risk assessmen...

Predicting early response to ablative radiotherapy in oligometastatic disease: a scoping review of radiomics-based machine learning and deep learning models.

OBJECTIVES: Oligometastatic disease represents an intermediate stage of cancer, often treated with surgery or ablative radiotherapy (ART). This scopin...

A quantitative analysis of global AI medical studies: gaps in randomized controlled trials.

Medical artificial intelligence (AI) has advanced rapidly, yet a comprehensive quantitative overview of its clinical evaluation landscape remains lack...

Machine and deep learning in REM sleep behavior disorder: a scoping review and analysis of reporting quality.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia, and its isolated form is of particular interest, as it is an early phase alpha...

Artificial intelligence versus human consensus: A concordance analysis in the screening of studies for evidence synthesis in physical activity and sport.

OBJECTIVE: To assess the agreement between the ChatGPT Plus (GPT 4.1) version and human consensus during the screening of studies in four different ev...

Editorial: future of ureteral stents: what do we need? a pearls opinion.

Ureteral stents, introduced in 1960s, are essential for managing upper urinary tract pathologies, maintaining ureteral patency in conditions like obst...

Machine learning-assisted multimodal lateral flow immunoassay based on urchin-like Au@Pt nanoparticles for quantitative determination of febuxostat in functional foods.

BACKGROUND: The illegal addition of febuxostat (FEB) to functional foods poses a significant food safety risk and calls for rapid and reliable analyti...