Surgery

Machine Learning-Enhanced TCAB Score for Predicting Postoperative Ischemic Stroke After CABG.

BACKGROUND: Postoperative acute ischemic stroke remains a critical complication of coronary artery bypass grafting. This study aimed to develop a novel Total Cerebral Atherosclerosis Burden (TCAB) score for predicting the risk of AIS post-coronary artery bypass grafting. METHODS: A prospective cohort of patients undergoing coronary artery bypass grafting was enrolled. The TCAB score was calculated...

Artificial Intelligence-Enabled Electrocardiographic Detection of Severe Aortic Stenosis Leading to Transcatheter Aortic Valve Replacement.

BACKGROUND: EchoNext is an artificial intelligence (artificial intelligence)-enabled electrocardiographic (ECG) model validated to detect unrecognized structural heart disease. FIRST-IN-HUMAN/EARLY REPORTS SUMMARY: An 84-year-old woman presented after a fall and was found to have a left femur fracture. An ECG was ordered which was analyzed by EchoNext. Despite the absence of cardiac symptoms, the ...

Explainable machine learning with routine biomarkers identifies culture-defined bacteremic urosepsis.

Urosepsis is a severe complication of urinary tract infection (UTI) and may lead to organ dysfunction and death. Early identification remains challeng...

Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling.

BACKGROUND: Labor pain is a major physiological and psychological stressor for women during childbirth. Epidural analgesia is widely recognized as the...

Bone Mineral Density of Spine Patients with CT Hounsfield Units and AI Segmentation: A Contemporary Review.

It is widely accepted that bone mineral density affects outcomes for spinal arthrodesis surgeries. Traditional techniques such as dual-energy X-ray ab...

Robot-Related Workers' Compensation Claims in Ohio, 2001-2020.

BACKGROUND: Increased robot adoption and advancements in robotics have led to the emergence of robotic arms for collaborative applications that work a...

Automating Virtual Dental Implant Placement: Can AI Match Clinical Expertise?

OBJECTIVES: This study evaluated a validated artificial intelligence (AI) tool for virtual implant planning by comparing its performance with expert-p...

Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.

The validation of promising clinical biomarkers, molecular mechanisms, and novel drug targets in cardiovascular disease (CVD) is hindered by a vast an...

A Multiomic Liquid Biopsy for the Earlier Detection of Colorectal Cancer.

UNLABELLED: Timely diagnosis and intervention in colorectal cancer are critical to improving patient outcomes and limiting disease progression. Screen...

Beyond BMI: Deep Learning Segmentation-Driven CT Reveals Body Composition Changes After Metabolic and Bariatric Surgery.

BACKGROUND: Body mass index (BMI) is the primary metric used to evaluate metabolic and bariatric surgery (MBS) outcomes but does not distinguish tissu...

Increased risk of neurodevelopmental impairment associated with reduced brain volume at term-equivalent age in preterm infants with germinal matrix hemorrhage.

ICP-WAVES: Intracranial Pressure Waveform Analysis and Visualization for Enhanced Signal Processing.

OBJECTIVE: Intracranial pressure (ICP) waveform morphology reflects brain compliance and cerebrospinal fluid dynamics. Existing monitoring methods fai...

Development and multicenter validation of an explainable machine learning diagnostic criteria for pediatric abdominal sepsis.

Accurate identification of early pediatric abdominal sepsis (PAS) is essential to improving outcomes, yet most existing pediatric sepsis criteria and ...

An ophthalmic video foundation model for surgical recognition and navigation with wet-lab porcine eye validation.

Foundation models in artificial intelligence are revolutionizing healthcare by utilizing large-scale unlabelled data for pretraining. However, their i...

Automated Measurement of Midpalatal Suture Density Ratio Based on Deep Learning.

Rapid maxillary expansion (RME) is a common method for maxillary transverse deficiency. While the midpalatal suture density (MPSD) ratio is a critical...

Attention-enhanced deep learning model for automated classification of hemorrhagic and ischemic stroke on CT imaging.

BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorrhagic stroke and ischemic stroke require completel...

Mapping Artificial Intelligence Research in Oral and Maxillofacial Surgery: A Bibliometric Analysis.

INTRODUCTION AND AIMS: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this f...

Application of a Natural Language Processing Framework for Data Extraction From Pathology Reports Across Multiple Cancer Types.

BACKGROUND: Pathological reports provide comprehensive insights into the clinical and pathological features of different cancer types. However, extrac...

Minimally invasive surgery for advanced-stage ovarian cancer: a review of evidence and emerging paradigms.

Minimally invasive surgery has emerged as a promising approach to the management of advanced-stage epithelial ovarian cancer, particularly in the sett...

Deep learning-based identification and maturation assessment of the zygomaticomaxillary suture in cone-beam computed tomography images.

OBJECTIVE: This study addresses maxillary deficiency management by developing a deep learning-based system for zygomaticomaxillary suture assessment. ...