Emergency Medicine

Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels.

BACKGROUND: Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (ICHs) on non-contrast enhanced cranial CT scans to manage the clinical care of these patients in a timelier fashion.

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach.

An ensemble model for predicting dispositions of emergency department patients.

OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department...

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots ...

Artificial intelligence diagnostic accuracy in fracture detection from plain radiographs and comparing it with clinicians: a systematic review and meta-analysis.

PURPOSE: Fracture detection is one of the most commonly used and studied aspects of artificial intelligence (AI) in medicine. In this systematic revie...

Application of machine learning and multivariate approaches for assessing microplastic pollution and its associated risks in the urban outdoor environment of Bangladesh.

Microplastics (MPs) are an emerging global concern due to severe toxicological risks for ecosystems and public health. Therefore, this is the first st...

Postoperative leukocyte counts as a surrogate for surgical stress response in matched robot- and video-assisted thoracoscopic surgery cohorts of patients: A preliminary report.

The objective is to preliminary evaluated postoperative leukocyte counts as a surrogate for the surgical stress response in NSCLC patients who underwe...

How artificial intelligence could transform emergency care.

Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically associated with clinical care (e.g. medical decisio...

Chemometrics-driven prediction and prioritization of diverse pesticides on chickens for addressing hazardous effects on public health.

The extensive use of various pesticides in the agriculture field badly affects both chickens and humans, primarily through residues in food products a...

Development and Internal Validation of a Multivariable Prediction Model for Mortality After Hip Fracture with Machine Learning Techniques.

In order to estimate the likelihood of 1, 3, 6 and 12 month mortality in patients with hip fractures, we applied a variety of machine learning methods...

An Automated Multi-scale Feature Fusion Network for Spine Fracture Segmentation Using Computed Tomography Images.

Spine fractures represent a critical health concern with far-reaching implications for patient care and clinical decision-making. Accurate segmentatio...

Harnessing machine learning to predict cytochrome P450 inhibition through molecular properties.

Cytochrome P450 enzymes are a superfamily of enzymes responsible for the metabolism of a variety of medicines and xenobiotics. Among the Cytochrome P4...

Effect of on neurological function in acute aneurysmal subarachnoid hemorrhage patients with high inflammation: A preliminary randomized, double-blind, placebo-controlled clinical trial.

BACKGROUND AND AIM: (AM) is a traditional Chinese herb. Our previous study revealed that AM can enhance neurological function in patients with acute ...

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 improving patient care. This study contributes to thi...

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 the pelvic bones. Timely diagnosis of pelvic fractur...

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 experiments. Computational techniques to acquire inform...

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 models (LLMs) have myriad potential applications in me...

Attention-based deep learning framework for automatic fundus image processing to aid in diabetic retinopathy grading.

BACKGROUND AND OBJECTIVE: Early detection and grading of Diabetic Retinopathy (DR) is essential to determine an adequate treatment and prevent severe ...

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 complications in the postoperative period are rare,...

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-based algorithms for identifying low acuity Emergency...