Surgery

Predictive Value of Geriatric Nutritional Risk Index and Risk Analysis Index for Post-operative Outcomes in Spine Surgery Patients: A Comprehensive Analysis.

Study DesignRetrospective cohort study.ObjectivesFrailty and nutritional status are predictors of adverse spine surgery outcomes. This study evaluated the predictive utility of a combined Risk Analysis Index (RAI) and Geriatric Nutritional Risk Index (GNRI) model, and introduced a compound score integrating RAI, GNRI, American Society of Anesthesiologists (ASA) classification, and Preoperative Acu...

Novel risk calculator predicting long-term survival in pediatric versus adult patients diagnosed with spinal low-grade glioma: a nationwide analysis.

BACKGROUND CONTEXT: Spinal low-grade gliomas (SLGGs) are rare, slow-growing central nervous system tumors affecting both pediatric and adult populations. Due to their rarity, their prognosis and optimal treatment strategies remain poorly defined, necessitating further investigation into age-related differences in outcomes and risk factors. PURPOSE: This study aims to evaluate differences in treatm...

Unsupervised machine learning to explore inflammation following cardiopulmonary bypass.

IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative ou...

Assessment of Multimodal Natural Language Processing in Ascertaining Perioperative Safety Indicators From Preoperative Notes in Spine Surgery.

INTRODUCTION: Standard spine surgery machine learning (ML) models often rely on structured clinical data, overlooking nuanced free text, such as preop...

Latest Developments in Artificial Intelligence and Machine Learning Models in General Pediatric Surgery.

Artificial intelligence (AI) and machine learning (ML) models rapidly transform health care with applications ranging from diagnostic image interpreta...

Does Laterality of the Caudal Septal Extension Graft Matter? A Photograph-Based Analysis of Symmetry in Rhinoplasty.

BACKGROUND: Ideal tip projection and rotation in rhinoplasty often requires placement of caudal septal extension grafts (CSEGs). Although CSEGs are ub...

Evaluating AI Responses to Postoperative Questions in Mohs Reconstruction.

INTRODUCTION: Patients frequently ask questions after Mohs facial reconstruction. AI tools, particularly large language models (LLMs), may optimize th...

Identification of key genes in intracranial aneurysm via WGCNA: insights into immune microenvironment and therapeutic targets.

BACKGROUND: Intracranial aneurysms (IA) are prevalent vascular lesions whose rupture causes subarachnoid hemorrhage with high disability and mortality...

Evaluating the diagnostic accuracy of AI in ischemic and hemorrhagic stroke: A comprehensive meta-analysis.

Stroke poses a significant health challenge, with ischemic and hemorrhagic subtypes requiring timely and accurate diagnosis for effective management. ...

Surgeon, Trainee, or GPT? A Blinded Multicentric Study of AI-Augmented Operative Notes.

OBJECTIVES: Clear, complete operative documentation is essential for surgical safety, continuity of care, and medico-legal standards. Large language m...

Use of Machine Learning to Derive Discrete Clinical Phenotypes and Assess Treatment-Effect Heterogeneity in the Steroids in Cardiac Surgery Trial Dataset.

BACKGROUND: Robust clinical trial data provide a key component for the development of evidence-informed medicine. However, clinical trial data may dem...

Machine Learning in Venous Thromboembolism-Why and What Next?

Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE a...

Machine learning models to predict postoperative incontinence after endoscopic enucleation of the prostate for benign prostatic hyperplasia: An EAU-Endourology study.

BACKGROUND: Machine learning (ML) and artificial intelligence (AI) have demonstrated powerful functionality in the healthcare setting thus far. We aim...

Using artificial intelligence as a technological tool in gynecologic and obstetric health: A narrative literature review.

Maternal mortality remains a critical global public health issue, particularly in low- and middle-income settings where failures in surveillance, earl...

Development and validation of the APEX-HBD SCORe: a multivariable prediction model for postoperative complications in patients undergoing shoulder arthroplasty.

BACKGROUND: The incidence of total shoulder arthroplasty (TSA) has risen significantly, driven by expanded indications. This study aims to derive and ...

Deep Learning-Based Prediction of Orthognathic Surgery Need in Skeletal Class II Patients Using Facial Profile Images: An Artificial Intelligence Study.

Orthognathic surgery is often required to address moderate to severe skeletal class II malocclusion, a condition that affects both facial aesthetics a...

Machine Learning-Driven Radiomic Profiling of Thalamus-Amygdala Nuclei for Prediction of Postoperative Delirium After STN-DBS in Parkinson's Disease Patients: A Pilot Study.

Postoperative delirium is a common complication following sub-thalamic nucleus deep brain stimulation surgery in Parkinson's disease patients. Postope...

Graph Neural Networks for Realistic Bleeding Prediction in Surgical Simulators.

This study presents a novel approach using graph neural networks to predict the risk of internal bleeding using vessel maps derived from patient CT an...

Efficacy of artificial intelligence for adenoma detection in water exchange colonoscopy: a two-center randomized controlled trial.

Water exchange and artificial intelligence-based computer-aided detection (CADe) separately improve the adenoma detection rate (ADR) and number of ade...

Can AI grade like a professor? comparing artificial intelligence and faculty scoring of medical student short-answer clinical reasoning exams.

Many medical schools primarily use multiple-choice questions (MCQs) in pre-clinical assessments due to their efficiency and consistency. However, whil...