Emergency Medicine

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for imp...

Enhancing fracture diagnosis in pelvic X-rays by deep convolutional neural network with synthesized images from 3D-CT.

Pelvic fractures pose significant challenges in medical diagnosis due to the complex structure of th...

Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.

Practical, legal, and ethical reasons necessitate the development of methods to replace animal exper...

Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.

BACKGROUND: Natural language processing (NLP) tools including recently developed large language mode...

Prostatic Fossa Pseudoaneurysm After Robot-Assisted Radical Prostatectomy (RARP): A Case Report.

BACKGROUND RARP is an established procedure in treatment of localized prostate cancer. Hemorrhagic c...

The new era of artificial intelligence in neuroradiology: current research and promising tools.

Radiology has a number of characteristics that make it an especially suitable medical discipline for...

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-bas...

Supervised representation learning based on various levels of pediatric radiographic views for transfer learning.

Transfer learning plays a pivotal role in addressing the paucity of data, expediting training proces...

Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and l...

Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning.

Technical complexity associated with biodegradation testing, particularly for substances of unknown ...

Machine Learning Identifies Higher Survival Profile In Extracorporeal Cardiopulmonary Resuscitation.

OBJECTIVES: Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologic...

[Orthopedics and trauma surgery in the digital age].

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedi...

Cost-Effectiveness of Artificial Intelligence-Based Opportunistic Compression Fracture Screening of Existing Radiographs.

PURPOSE: Osteoporotic vertebral compression fractures (OVCFs) are a highly prevalent source of morbi...

New technology, psychiatry, and the law: Panic, prudence, possibility.

Throughout human history, all new technology has been met with surprise, anxiety, panic, and - event...

Artificial intelligence to advance acute and intensive care medicine.

PURPOSE OF REVIEW: This review explores recent key advancements in artificial intelligence for acute...

Enhanced skin burn assessment through transfer learning: a novel framework for human tissue analysis.

Visual inspection is the typical way for evaluating burns, due to the rising occurrence of burns glo...

Deus Ex Machina? The Rise of Artificial Intelligence in Toxicology.

Artificial intelligence (AI) is rising rapidly, driven by big data, complex algorithms, and computin...

Methodological issues on precision and prediction value of ChatGPT in emergency department triage decisions.

The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations.

Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico...

In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning.

Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to ...

Early identification of suspected serious infection among patients afebrile at initial presentation using neural network models and natural language processing: A development and external validation study in the emergency department.

OBJECTIVE: To develop and externally validate models based on neural networks and natural language p...