Domestic Violence

Incorporating standardised reporting guidelines in clinical trials of artificial intelligence in gastrointestinal endoscopy.

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials. Its widespre...

Guiding better design and reporting of AI-intervention trials.

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension.

The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines ...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension.

The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement a...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespre...

Identifying normal mammograms in a large screening population using artificial intelligence.

OBJECTIVES: To evaluate the potential of artificial intelligence (AI) to identify normal mammograms ...

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Cen...

Quantifying drug tissue biodistribution by integrating high content screening with deep-learning analysis.

Quantitatively determining in vivo achievable drug concentrations in targeted organs of animal model...

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Breast cancer screening has been shown to significantly reduce mortality in women. The increased uti...

Deep learning-based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals.

OBJECTIVES: Performance of deep learning-based automated detection (DLAD) algorithms in systematic s...

Improved Scaffold Hopping in Ligand-Based Virtual Screening Using Neural Representation Learning.

Deep learning has demonstrated significant potential in advancing state of the art in many problem d...

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

METHODS: We collected and sorted out the white light endoscopic images of some patients undergoing c...

Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study.

BACKGROUND: Maternal serum alpha-fetoprotein (MSAFP) concentration typically increases during pregna...

Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies.

The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-...

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses.

OBJECTIVE: Emergency department (ED) return visits within 72 h may be a sign of poor quality of care...

Thyroid Ultrasound Reports: Will the Thyroid Imaging, Reporting, and Data System Improve Natural Language Processing Capture of Critical Thyroid Nodule Features?

BACKGROUND: Critical thyroid nodule features are contained in unstructured ultrasound (US) reports. ...

New convolutional neural network model for screening and diagnosis of mammograms.

Breast cancer is the most common cancer in women and poses a great threat to women's life and health...

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can ...