Latest AI and machine learning research in emergency medicine for healthcare professionals.
STUDY OBJECTIVE: There is increasing interest in harnessing artificial intelligence to virtually triage patients seeking care. The objective was to examine the reliability of a virtual machine learning algorithm to remotely predict acuity scores for patients seeking emergency department (ED) care by applying the algorithm to retrospective ED data.
Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite tremendous effort, machine learning prediction of protein solubility changes upon mutation remains a challenging task as indicated by the poor scores of normalized Correct Prediction Ratio (CPR). Part of the challenge stems from the fact that there is ...
Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-ma...
This study aimed to explore the correlation between serum creatinine and burn severity and the value of predicting the outcome of patients. For this p...
A sizable percentage of the population in India still does not have easy access to dental facilities. Therefore, it is of interest to document the rol...
BACKGROUND AND OBJECTIVE: The Children's Early Warning Tool (CEWT), developed in Australia, is widely used in many countries to monitor the risk of de...
INTRODUCTION: The application of Artificial Intelligence (AI) to predictive toxicology is rapidly increasing, particularly aiming to develop non-testi...
(1) Background: We aimed to investigate the effect of change in pre-wash and post-wash semen parameters on intrauterine insemination (IUI) success in ...
OBJECTIVE: Traditional manual OLIF combined with pedicle screw implantation has many problems of manual percutaneous screw implantation, such as high ...
In 2022, a global outbreak of Mpox (formerly monkeypox) occurred in various countries across Europe and America and rapidly spread to more than 100 co...
Minimally invasive surgery (MIS) in gynecology was introduced to achieve the same surgical objectives as traditional open surgery while minimizing tra...
Papilledema is a pathology delineated by the swelling of the optic disc secondary to raised intracranial pressure (ICP). Diagnosis by ophthalmoscopy c...
BACKGROUND: Subarachnoid hemorrhage (SAH) entails high morbidity and mortality rates. Convolutional neural networks (CNN) are capable of generating hi...
OBJECTIVES: To predict the functional outcome of patients with intracerebral hemorrhage (ICH) using deep learning models based on computed tomography ...
Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's deadliest diseases. Most deaths are among persons with TB ...
Preterm birth (PTB) affects approximately 10% of births globally each year and is the most significant direct cause of neonatal death and of long-term...
INTRODUCTION: In the field of pediatric trauma computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems have emerged offering a pro...
OBJECTIVE: Recent systematic reviews of acute care medicine applications of artificial intelligence (AI) have focused on hospital and general prehospi...