Emergency Medicine

Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strategies in the early stages of drug development for human toxicity assessment. At present, artificial intelligence methods are popularly regarded as a promising solution in chemical toxicology. Thus, we provided comprehensive prediction models for eight...

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

BACKGROUND: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED...

Crowd-Sourced Deep Learning for Intracranial Hemorrhage Identification: Wisdom of Crowds or Laissez-Faire.

BACKGROUND AND PURPOSE: Researchers and clinical radiology practices are increasingly faced with the task of selecting the most accurate artificial in...

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. Internal hemorrhage can be rapidly diagnosed by findi...

Robot Assisted Laparoscopy Combined with Thoracoscopy in the Treatment of Hepatocellular Carcinoma with Inferior Vena Cava Tumor Thrombus.

BACKGROUND: Facing the 0.7-22% incidence rate of hepatocellular carcinoma (HCC) with inferior vena cava tumor thrombus (IVCTT), there are usually no o...

Probabilistic real-time natural gas jet fire consequence modeling of offshore platforms by hybrid deep learning approach.

Natural gas jet fire induced by igniting blowouts has the potential to cause critical structure damage and great casualties of offshore platforms. Rea...

The evolution and development of a robotic acute care surgery program.

BACKGROUND: Acute care surgeons perform more than 850,000 operations annually on emergency general surgery patients in the United States. Emergency ge...

Erroneous electrocardiographic interpretations and its clinical implications.

INTRODUCTION: The advancement of artificial intelligence (AI) has aided clinicians in the interpretation of electrocardiograms (ECGs) serving as an es...

[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].

BACKGROUND: High expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma ...

Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection.

PURPOSE: Most studies evaluating artificial intelligence (AI) models that detect abnormalities in neuroimaging are either tested on unrepresentative p...

Development of a Deep Learning Model for Retinal Hemorrhage Detection on Head Computed Tomography in Young Children.

IMPORTANCE: Abusive head trauma (AHT) in children is often missed in medical encounters, and retinal hemorrhage (RH) is considered strong evidence for...

The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Arti...

Advancing Computational Toxicology by Interpretable Machine Learning.

Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals have a critical impact on human health. Traditional animal mod...

Reconstructive Allograft Preparation for Long Bone Intercalary Segments After Tumor Resections: Toronto Sarcoma Protocol.

BACKGROUND: The Reconstructive Allograft Preparation by Toronto Sarcoma (RAPTORS) protocol is reliable and reproducible without substantially adding t...

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding...

Real-World Performance of Large Vessel Occlusion Artificial Intelligence-Based Computer-Aided Triage and Notification Algorithms-What the Stroke Team Needs to Know.

PURPOSE: To evaluate the real-world performance of two FDA-approved artificial intelligence (AI)-based computer-aided triage and notification (CADt) d...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. This study aimed to summarize the current application...

Effects of da Vinci robot versus thoracoscopic surgery on body trauma and lymphocyte subsets in lung cancer patients: A propensity score matching study.

BACKGROUND: To assess the impact of da Vinci robot versus thoracoscopic surgery on body trauma and lymphocyte subsets in lung cancer patients.

Henry gas solubility optimization double machine learning classifier for neurosurgical patients.

This study aims to predict head trauma outcome for Neurosurgical patients in children, adults, and elderly people. As Machine Learning (ML) algorithms...

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We a...