Domestic Violence

Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction.

The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-res...

Radioport: a radiomics-reporting network for interpretable deep learning in BI-RADS classification of mammographic calcification.

Generally, due to a lack of explainability, radiomics based on deep learning has been perceived as a...

Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people wi...

Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, c...

Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained attention because of its pot...

Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?

Colorectal cancer is a significant global health concern, necessitating effective screening strategi...

Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis.

PURPOSE: To evaluate the diagnostic accuracy of artificial intelligence (AI)-based automated diabeti...

Telemedicine-Enhanced Lung Cancer Screening Using Mobile Computed Tomography Unit with Remote Artificial Intelligence Assistance in Underserved Communities: Initial Results of a Population Cohort Study in Western China.

.

Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting a...

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain ...

Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making ...

Deep-learning image analysis for high-throughput screening of opsono-phagocytosis-promoting monoclonal antibodies against Neisseria gonorrhoeae.

Antimicrobial resistance (AMR) is nowadays a global health concern as bacterial pathogens are increa...

Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.

During an artificial intelligence (AI)-assisted diabetic retinopathy screening event, we performed a...

An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening.

Since structural analyses and toxicity assessments have not been able to keep up with the discovery ...

Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.

OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over ...

Deep learning model for the detection of prostate cancer and classification of clinically significant disease using multiparametric MRI in comparison to PI-RADs score.

BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) is an established reporting sch...

Kinome-Wide Virtual Screening by Multi-Task Deep Learning.

Deep learning is a machine learning technique to model high-level abstractions in data by utilizing ...

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (...

Some suggestions for 'A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (AITEL) research in medical education'.

Meta-research on reporting guidelines for artificial intelligence: are authors and reviewers encouraged enough in radiology, nuclear medicine, and medical imaging journals?

PURPOSE: To determine how radiology, nuclear medicine, and medical imaging journals encourage and ma...

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the ...