Domestic Violence

Revolution of echocardiographic reporting: the new era of artificial intelligence and natural language processing.

Artificial intelligence (AI) has been making a significant impact on cardiovascular imaging, transfo...

Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data.

INTRODUCTION: Time- and resource-demanding activities related to processing individual case safety r...

CoAt-Mixer: Self-attention deep learning framework for left ventricular hypertrophy using electrocardiography.

Left ventricular hypertrophy is a significant independent risk factor for all-cause mortality and mo...

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults.

Abdominal ultrasonography has become an integral component of the evaluation of trauma patients. Int...

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval.

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingl...

Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease.

BACKGROUND: Information on electrocardiogram (ECG) has not been quantified in obstructive coronary a...

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.

BACKGROUND: International societies have issued guidelines for high-risk breast cancer (BC) screenin...

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data.

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic ...

Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives.

A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting pressur...

Applying deep learning to iterative screening of medium-sized molecules for protein-protein interaction-targeted drug discovery.

We combined a library of medium-sized molecules with iterative screening using multiple machine lear...

Large language models for structured reporting in radiology: performance of GPT-4, ChatGPT-3.5, Perplexity and Bing.

Structured reporting may improve the radiological workflow and communication among physicians. Artif...

Genomic and machine learning-based screening of aquaculture-associated introgression into at-risk wild North American Atlantic salmon (Salmo salar) populations.

The negative genetic impacts of gene flow from domestic to wild populations can be dependent on the ...

Screening outcome for interpretation by the first and second reader in a population-based mammographic screening program with independent double reading.

BACKGROUND: Double reading of screening mammograms is associated with a higher rate of screen-detect...

Invited Commentary: Transparent reporting of artificial intelligence models development and evaluation in surgery: The TRIPOD and DECIDE-AI checklists.

A real-world evaluation of the implementation of NLP technology in abstract screening of a systematic review.

The laborious and time-consuming nature of systematic review production hinders the dissemination of...

Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment....

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) syste...

Opportunistic Screening: Scientific Expert Panel.

Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunis...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

Deep learning technology has been used in the medical field to produce devices for clinical practice...

A family-centered orthodontic screening approach using a machine learning-based mobile application.

BACKGROUND/PURPOSE: Skeletal orthodontic deformities can have functional and aesthetic consequences,...

Virtual Screening of Nrf2 Dietary-Derived Agonists and Safety by a New Deep-Learning Model and Verified and .

Nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is an essential regulatory target of antioxidants...