Domestic Violence

Decision effect of a deep-learning model to assist a head computed tomography order for pediatric traumatic brain injury.

The study aims to measure the effectiveness of an AI-based traumatic intracranial hemorrhage prediction model in the decisions of emergency physicians regarding ordering head computed tomography (CT) scans. We developed a deep-learning model for predicting traumatic intracranial hemorrhages (DEEPTICH) using a national trauma registry with 1.8 million cases. For simulation, 24 cases were selected f...

Deep learning for automatic brain tumour segmentation on MRI: evaluation of recommended reporting criteria via a reproduction and replication study.

OBJECTIVES: To determine the reproducibility and replicability of studies that develop and validate segmentation methods for brain tumours on MRI and that follow established reproducibility criteria; and to evaluate whether the reporting guidelines are sufficient.

Collaborative deep learning model for tooth segmentation and identification using panoramic radiographs.

Panoramic radiographs are an integral part of effective dental treatment planning, supporting dentists in identifying impacted teeth, infections, mali...

Machine Learning in the Prediction of Trauma Outcomes: A Systematic Review.

STUDY OBJECTIVE: Machine learning models carry unique potential as decision-making aids and prediction tools for improving patient care. Traumatically...

AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists.

Artificial intelligence (AI) has been recognized as a powerful technique that can accelerate drug discovery during the hit compound identification ste...

Automated image curation in diabetic retinopathy screening using deep learning.

Diabetic retinopathy (DR) screening images are heterogeneous and contain undesirable non-retinal, incorrect field and ungradable samples which require...

Deep Learning for FAST Quality Assessment.

OBJECTIVES: To determine the feasibility of using a deep learning (DL) algorithm to assess the quality of focused assessment with sonography in trauma...

Added value of an artificial intelligence solution for fracture detection in the radiologist's daily trauma emergencies workflow.

PURPOSE: The main objective of this study was to compare radiologists' performance without and with artificial intelligence (AI) assistance for the de...

Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer.

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in t...

Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study.

BACKGROUND: The Paris System for Reporting Urinary Cytology (TPS) has been shown to improve bladder cancer diagnosis. Advances in artificial intellige...

New Robotic System with Wristed Microinstruments Allows Precise Reconstructive Microsurgery: Preclinical Study.

BACKGROUND: Microsurgery allows complex reconstruction of tissue defects after oncological resections or severe trauma. Performing these procedures ma...

Deep learning for emergency ascites diagnosis using ultrasonography images.

PURPOSE: The detection of abdominal free fluid or hemoperitoneum can provide critical information for clinical diagnosis and treatment, particularly i...

Deep-learning synthesized pseudo-CT for MR high-resolution pediatric cranial bone imaging (MR-HiPCB).

PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop ...

Multi-branch fusion auxiliary learning for the detection of pneumonia from chest X-ray images.

Lung infections caused by bacteria and viruses are infectious and require timely screening and isolation, and different types of pneumonia require dif...

Deep learning for behaviour classification in a preclinical brain injury model.

The early detection of traumatic brain injuries can directly impact the prognosis and survival of patients. Preceding attempts to automate the detecti...

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetit...

Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations.

Background A deep learning (DL) model to identify lung cancer screening candidates based on their chest radiographs requires external validation with ...

The Role of AirSeal in Robotic Urologic Surgery: A Systematic Review.

The adoption of a valveless trocar system in robotic surgery has allowed for stable pneumoperitoneum and constant smoke evacuation. The reported bene...

The current status of robotic colorectal surgery training programmes.

Robotic-assisted colorectal surgery (RACS) is steadily increasing in popularity with an annual growth in the number of colorectal procedures undertake...

Application of Imaging Examination Based on Deep Learning in the Diagnosis of Viral Senile Pneumonia.

Medical image classification technology, preferably which is based on the deep learning, is not only a key auxiliary diagnosis and treatment method in...