Surgery

An In-Hospital Mortality Risk Model for Patients Undergoing Coronary Artery Bypass Grafting Based on Machine Learning: Cohort Study.

BACKGROUND: Ischemic heart disease remains the leading cause of death worldwide. Coronary artery bypass grafting (CABG) remains the primary surgical treatment for ischemic heart disease. There is currently a lack of highly accurate and widely applicable models for assessing the risk of postoperative mortality following CABG. OBJECTIVE: This study aimed to develop and validate an in-hospital mortal...

Machine learning model-guided selective use of temporary diverting ileostomy in rectal cancer surgery: a randomized controlled trial.

The appropriate use of temporary diverting ileostomy (TDI) in rectal cancer surgery lacks standardized criteria. A randomized controlled trial was performed to evaluate whether the Risk-Guided Temporary Ileostomy Decision (RTID) system, a machine learning-based anastomotic leakage (AL) prediction model, could improve the suitability of TDI utilization. A total of 872 patients with stage I-III rect...

AI based prediction of post prostatectomy urinary incontinence and its impact on quality of life: development and validation study.

Urinary incontinence can affect up to 53% of patients after radical prostatectomy, yet prediction tools rely on binary outcomes, missing heterogeneous...

External validity of deep learning solution for spontaneous intracranial hemorrhage detection on head CT scans.

We externally validated the performance of deep learning (DL) solution for detection of spontaneous intracerebral (ICH), intraventricular (IVH) and su...

Predicting response to neoadjuvant chemotherapy combined with immunotherapy in gastric cancer based on habitat imaging and peritumoral radiomics: a two-center study.

BACKGROUND: Predicting pathological response to neoadjuvant chemotherapy combined with immunotherapy (NACI) in locally advanced gastric cancer (LAGC) ...

Extended reality and emerging artificial intelligence in orthopedic surgical training: a scoping review of educational outcomes.

Immersive technologies have gained increasing relevance in orthopedic surgical education; however, the scope, outcomes, and maturity of extended reali...

Blood Transcriptomic Signatures Distinguish Mycobacterium avium Complex Pulmonary Disease from Colonization: A Multicenter Cohort Study.

AbstractPulmonary infections caused by nontuberculous mycobacteria (NTM), particularly Mycobacterium avium complex (MAC), are increasingly recognized ...

LUCID: An AI-Powered System for Real-Time Laparoscopic Lens Cleanliness Classification.

BackgroundIn minimally invasive surgery (MIS), maintaining consistent optical clarity is essential for surgical safety and efficiency. However, lens c...

Clin-STAR Corner: Practice Changing Advances at the Interface of Artificial Intelligence/Machine Learning and Geriatrics.

Artificial intelligence (AI) methods, including machine learning (ML), are transforming healthcare by enabling personalized interventions that integra...

SurgWound-Bench: a benchmark for surgical wound diagnosis.

Surgical site infection (SSI) is one of the most common and costly healthcare-associated infections, and surgical wound care remains a significant cha...

Estimating temporal treatment-effect patterns of radiotherapy and chemotherapy in lower-grade gliomas using causal machine learning.

Treatment decisions for lower-grade gliomas (WHO grades 2-3) rest on trial averages, which lack temporal resolution. We applied Causal Analysis of Sur...

Cataract-LMM Large-Scale Multi-Source Multi-Task Benchmark for Deep Learning in Surgical Video Analysis.

Computer-assisted surgery research requires large, deeply annotated video datasets that capture clinical and technical variability. Existing cataract ...

Integration of a collaborative robotic platform in laparoscopic cholecystectomy: safety, feasibility, and operative time variability.

Laparoscopic cholecystectomy is a high-volume procedure with relatively short operative times, leaving limited margin for further reduction in mean du...

AI-based automated bleeding monitoring in conventional and robot-assisted laparoscopic surgery: a systematic review.

Artificial intelligence has emerged as a promising approach for improving the detection and management of intraoperative bleeding during conventional ...

Discriminative features and contextual cognitive bias effects between robotic and natural handwriting.

This study aims to systematically identify the discriminative features between robotic and natural handwriting and explore how contextual conditions i...

Assessing Large Language Models for Clinical Coding in Hand Surgery: Effect of Note Authorship, Prompt Design, and Diagnosis/Procedure Type.

BACKGROUND: This study sought to assess large language models' (LLM) ability to generate correct ICD-10 and CPT codes using clinical documentation, an...

Learning-based fault-tolerant control for flexible joint robotic manipulators: An actor-critic framework with experimental verification.

Flexible-joint robotic manipulators (FJRMs) offer significant advantages over traditional rigid-link counterparts, including improved dexterity, great...

Treatment effect heterogeneity of radiotherapy in localized Ewing sarcoma: A secondary analysis of the EURO-E.W.I.N.G. 99 and Ewing 2008 trial.

INTRODUCTION: Standard Ewing sarcoma treatment includes chemotherapy and local therapy. Previous studies found no average treatment effect of combined...

Identification of diagnostic markers for diabetic kidney disease by weighted gene co‑expression network analysis and machine learning.

Diabetic kidney disease (DKD) represents a major complication associated with diabetes mellitus, notably contributing to patient morbidity and mortali...

Interpretable machine learning to predict postoperative adverse outcomes in cardiac surgery.

BACKGROUND: Cardiac surgery is associated with significant mortality and complication risks. This study aims to develop an interpretable machine learn...