Surgery

Cross-Continental Transfer of Perioperative Mortality Prediction: Intraoperative Features Generalize Where Preoperative Features Fail

Machine learning models for perioperative mortality prediction show strong internal discrimination, yet external validation—particularly across continents—remains rare. Whether intraoperative vital sign features, which improve internal performance by 5–10%, transfer across populations is unknown. Furthermore, aggregate discrimination metrics may overstate clinical utility through Simpson’s paradox...

Transcriptome profiling to identify blood biomarkers for peritoneal endometriosis

Peritoneal endometriosis (PE) remains challenging to diagnose, as it cannot be detected using standard imaging modalities and no clinically validated biomarkers are available. To identify novel blood-based biomarkers for PE using whole blood transcriptomics combined with machine learning approaches. This observational study enrolled 48 women undergoing laparoscopic surgery for endometriosis-relate...

Multitask Artificial Intelligence–Based Electrocardiogram Tool for Preoperative Cardiac Testing in Noncardiac Surgery: Retrospective Cohort Study of Health Care Utilization and Costs

Preoperative cardiovascular (CV) risk stratification is essential in non-cardiac surgery, but conventional testing is frequently overused, increasing ...

Operational Survival Deficit of Neoadjuvant Chemotherapy in Early-Stage Breast Cancer: A Target Trial Emulation and Causal Machine Learning Study

Neoadjuvant chemotherapy (NAC) is the standard of care for locally advanced breast cancer. However, the disconnect between efficacy in randomized tria...

Development and Evaluation of Machine Learning Models to Predict Mechanical Restraint and Related Coercive Measures in Hospital Psychiatry

Use of coercive measures in psychiatric hospitals is clinically and ethically challenging. Aiming to support prevention, we developed and evaluated ma...

DeepCRI: Real-time EEG-based Prognostication after Cardiac Arrest

Accurate prediction of neurological outcome after cardiac arrest is essential for guiding intensive care decisions. Electroencephalography (EEG) suppo...

Cerebral Cortical Reorganization After Intracerebral Hemorrhage in Children

Structural changes following pediatric intracerebral hemorrhage (ICH) caused by ruptured brain vascular malformations remain poorly understood. We con...

Evaluation of SSI risk prediction model after spinal surgery: A systematic review and critical appraisal

This study aimed to systematically review and critically evaluate the risk of bias and applicability of surgical site infection (SSI) risk prediction ...

Comparing the Treatment and Side Effects of Existing Bariatric Surgery Procedures: An Observational Study

Bariatric surgery is an established treatment for obesity and its associated comorbidities, including diabetes, hypertension, sleep apnea, and hyperch...

Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system.

OBJECTIVE: To assess the feasibility and efficacy of developing a predictive model for postoperative recurrence and metastasis in breast cancer using ...

Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as infection.

BACKGROUND: The annual incidence of upper gastrointestinal hemorrhage (UGIB) is about 60 cases/100,000 people, and about 40% of UGIB patients have hem...

Predicting postoperative malnutrition in patients with oral cancer: development of an XGBoost model with SHAP analysis and web-based application.

BACKGROUND: Postoperative malnutrition, which significantly affects recovery and overall quality of life, is a critical concern for patients with oral...

Donor-specific digital twin for living donor liver transplant recovery.

The remarkable capacity of the liver to regenerate its lost mass after resection makes living donor liver transplantation a successful treatment optio...

Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model.

BACKGROUND: Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and...

Advanced multi-objective trajectory planning for robotic arms using a multi-strategy enhanced NSGA-II algorithm.

Facing the problems of large-scale rapid and disorderly loading, the robotic arm has the problems of large start-stop impact, easy to shake, and reduc...

Machine learning for early prediction of the infection in patients with urinary stone after treatment of holmium laser lithotripsy.

Patients after holmium laser lithotripsy have a certain probability of getting postoperative infection. An early and accurate diagnosis of postoperati...

Research on path planning of robotic arms based on DAPF-RRT algorithm.

In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random n...

Just another tool in their repertoire: uncovering insights into public and patient perspectives on clinicians' use of machine learning in perioperative care.

OBJECTIVES: Successful implementation of machine learning-augmented clinical decision support systems (ML-CDSS) in perioperative care requires the pri...

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2...

PROGNOSTIC ACCURACY OF MACHINE LEARNING MODELS FOR IN-HOSPITAL MORTALITY AMONG CHILDREN WITH PHOENIX SEPSIS ADMITTED TO THE PEDIATRIC INTENSIVE CARE UNIT.

Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The ad...