Surgery

Evaluating the generalizability of video-based assessment of intraoperative surgical skill in capsulorhexis.

PURPOSE: Assessment of intraoperative surgical skill is necessary to train surgeons and certify them for practice. The generalizability of deep learning models for video-based assessment (VBA) of surgical skill has not yet been evaluated. In this work, we evaluated one unsupervised domain adaptation (UDA) and three semi-supervised (SSDA) methods for generalizability of models for VBA of surgical s...

Machine learning models in the prediction of chronic or shunt-dependent hydrocephalus following subarachnoid hemorrhage: A systematic review and meta-analysis.

PurposeChronic or shunt-dependent hydrocephalus is a frequent consequence of subarachnoid hemorrhage (SAH) with an unclear pathophysiology, making treatment challenging. Despite favorable outcomes following cerebrospinal fluid (CSF) diversion, high-risk surgical interventions remain necessary in some cases. Accurate prediction of chronic or shunt-dependent hydrocephalus in SAH patients can play an...

Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study.

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) ranks among the most prevalent cancers worldwide, with early postoperative recurrence remaining a ma...

A Machine Learning Model to Predict Postoperative Speech Recognition Outcomes in Cochlear Implant Recipients: Development, Validation, and Comparison with Expert Clinical Judgment.

: Cochlear implantation (CI) significantly enhances speech perception and quality of life in patients with severe-to-profound sensorineural hearing lo...

Development of Explainable Machine Learning Models to Identify Patients at Risk for 1-Year Mortality and New Distant Metastases Postendoprosthetic Reconstruction for Lower Extremity Bone Tumors: A Secondary Analysis of the PARITY Trial.

BACKGROUND: Accurate prediction of postoperative metastasis and mortality risks in patients undergoing lower-limb oncological resection and endoprosth...

Performance of multimodal prediction models for intracerebral hemorrhage outcomes using real-world data.

BACKGROUND: We aimed to develop and validate multimodal models integrating computed tomography (CT) images, text and tabular clinical data to predict ...

Genetic Risk Scores in Stroke Research and Care.

Stroke remains a leading cause of death and disability worldwide. While well-established risk factors play a major role, genetic predisposition is a c...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 2. COMI item-content, scoring, language versions, and applications.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 1. Development of the COMI, interpretation of scores, and use in research.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

A machine learning model using echocardiographic myocardial strain to detect myocardial ischemia.

Coronary functional assessment plays a critical role in guiding decisions regarding coronary revascularization. Traditional methods for evaluating fun...

UKF-based model parameter estimation to localize the seizure onset zone in ECoG.

Drug-resistant epilepsy (DRE) patients typically require surgical intervention or neurostimulation. Therefore, accurate localization of the seizure on...

Phase recognition in manual Small-Incision cataract surgery with MS-TCN + + on the novel SICS-105 dataset.

Manual Small-Incision Cataract Surgery (SICS) is a prevalent technique in low- and middle-income countries (LMICs) but understudied with respect to co...

A Machine Learning Method for Predicting Acute Kidney Injury in Patients with Intracranial Hemorrhage.

Intracranial hemorrhage (ICH) is a critical and urgent condition in clinical practice. Recent research has highlighted acute kidney injury (AKI) that ...

Advances in virtual surgical planning for free tissue transfer.

PURPOSE OF REVIEW: This review seeks to describe the current state of virtual surgical planning (VSP) for head and neck free flap reconstruction, high...

Zero-shot large language model application for surgical site infection auditing.

INTRODUCTION: Artificial intelligence, in particular large language models (LLM), may be able to assist with monitoring for surgical site infections (...

Radiomics and AI-Based Prediction of MGMT Methylation Status in Glioblastoma Using Multiparametric MRI: A Hybrid Feature Weighting Approach.

: Glioblastoma (GBM) is a highly aggressive primary central nervous system tumor with a median survival of 14 months. MGMT (O6-methylguanine-DNA methy...

Data-driven identification of urgent surgical procedures for use in trauma outcomes measurement.

BACKGROUND: No standardized list of urgent-trauma-surgery exists for analysis in injury studies. If coded by a standard classification system, such a ...

Predicting Postoperative Blood Transfusion in Elderly Patients Undergoing Total Hip and Knee Arthroplasty Using Machine Learning Models.

PURPOSE: With the aging population, the demand for total hip arthroplasty (THA) and total knee arthroplasty (TKA) has risen significantly. Elderly pat...

External validation of the Oncotype DX breast cancer recurrence score nomogram and development and validation of a novel machine learning-based model to predict postoperative overall survival and guide adjuvant chemotherapy in ER positive, Her-2 negative breast cancer patients: a retrospective cohort study.

BACKGROUND: This study aims to externally validate the performance of the Oncotype DX (ODX) breast cancer (BC) recurrence score nomogram in predicting...

Cerebral ischemia detection using deep learning techniques.

Cerebrovascular accident (CVA), commonly known as stroke, stands as a significant contributor to contemporary mortality and morbidity rates, often lea...