Surgery

Digital twin-assisted surgery: technological architecture, integration across surgical phases, implementation challenges and future directions.

Digital twin-assisted surgery referred to the use of a dynamic, patient specific virtual model that mirrored physical patient in real time to enhance surgical planning, guidance, and outcomes. This emerging approach integrated data from robotic manipulators, intelligent implants, biosensors, and imaging systems to create a continuously updated digital representation that responded to physiological...

TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study.

BACKGROUND: Preoperative differentiation of precursor glandular lesions (PGL), minimally invasive (MIA), and invasive adenocarcinoma (IAC) in stage IA lung adenocarcinoma (LUAD) is critical for surgical planning but remains challenging due to overlapping CT features and interobserver variability. While existing artificial intelligence (AI) models focus predominantly on binary classification with l...

Expanded Indications in Advanced Endoscopic Resection of Malignant Gastrointestinal Lesions.

PURPOSE OF REVIEW: Endoscopic resection (ER) has transformed the management of early gastrointestinal (GI) malignancies by offering curative treatment...

Using AI Algorithms and Machine Learning in the Analysis of a Bio-Purification Method (Therapeutic Emesis, Known as "Vamana Karma"): Protocol for a Mixed Methods Study.

BACKGROUND: Therapeutic emesis (TE), known as vamana karma, is a classical method of detoxification performed to eliminate vitiated kapha (bio-humor g...

Integrating body composition analysis and machine learning for non-invasive identification of metabolic dysfunction-associated fatty liver disease: a large-scale health examination-based study.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a highly prevalent liver condition closely linked to obesity, insulin resistance, and ...

Noninvasive prediction of occult pT3a upstaging in localized ccRCC with radiogenomic insights and prognostic relevance.

Occult pathological T3a (pT3a) upstaging in cT1b-T2a clear cell renal cell carcinoma (ccRCC) correlated with poor prognosis and necessitated modificat...

Machine Learning Models for Predicting Stroke-Associated Pneumonia: A Systematic Review and Meta-Analysis.

Stroke-associated pneumonia (SAP) is a frequent and severe complication following stroke. Recently, several machine learning (ML) models have been dev...

AI Agent for Delirium Screening among Patients in Oncology and Cardiac Intensive Care Units: A Proof-of-Concept Study.

AIM: To develop and evaluate an autonomous artificial intelligence (AI) agent to support nurse-led delirium screening and guideline-concordant prevent...

Study design for an emulated trial of a 2 arm, parallel, stratified, adaptive, RCT of CABG versus PCI in people requiring myocardial revascularization at high risk (High-Risk REVASC).

AIM: This study aims to use routinely collected health data and trial emulation methodology to inform the design of a pragmatic randomized controlled ...

Reablation of atrial fibrillation targeting electrogram dispersion in patients with isolated veins: The RESTART trial.

BACKGROUND: Pulmonary vein (PV) isolation is a well-established treatment for atrial fibrillation (AF), however, strategies for patients with recurren...

Development and Assessment of a Custom GPT-4o Chatbot for Postoperative Counseling and Frequently Asked Questions in Breast Surgery Patients.

PURPOSE: Chatbots have an impressive ability to answer patient inquiries and assist medical personnel, but they are limited by specialty-specific know...

Development of machine learning-driven non-invasive diagnostic models for idiopathic membranous nephropathy in Chinese patients.

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a major cause of nephrotic syndrome and end-stage renal disease, but the gold-standard diagnost...

Development and multicentre validation of an artificial intelligence electrocardiogram model for ventricular remodeling in repaired tetralogy of Fallot.

AIMS: Periodic cardiac MRI (CMR) is recommended to identify adverse ventricular remodelling in repaired tetralogy of Fallot (TOF), but access to CMR i...

Interpretable machine learning reveals phosphorus-to-albumin ratio as a novel predictor of mortality and acute kidney injury in critically ill pancreatitis patients: a multi-center retrospective analysis.

Acute kidney injury (AKI), a common and severe complication of acute pancreatitis (AP), is amenable to early intervention. Phosphorus-to-albumin ratio...

Augmenting Surgical Preparation: How Learners Use Artificial Intelligence to Prepare for the Operating Room.

INTRODUCTION: Surgical trainees are increasingly using large language models (LLMs) for clinical and surgical preparation. However, there has been les...

Development of a Machine-Learning Model for Predicting Postoperative Complication Occurrence After Radical Gastrectomy Using Electronic Medical Records.

This study aims to develop a machine-learning model using electronic medical records to predict postoperative complications after radical gastrectomy ...

Risk Factors for Postoperative Delirium in Nonintensive Care Unit Patients: Machine Learning Approach.

Postoperative delirium is a frequent and serious complication lacking effective prediction tools for general ward patients. This study aimed to identi...

Hematologic markers and machine learning in predicting placenta accreta: A case-control study.

OBJECTIVE: This study aims to enhance antenatal detection of placenta accreta spectrum (PAS) and predict severe hemorrhage at delivery using machine l...

Forecasting Local Surges in COVID-19 Hospitalizations through Adaptive Decision Tree Classifiers.

IntroductionDuring the COVID-19 pandemic, many communities across the United States experienced surges in hospitalizations, which strained the local h...

Total Nasal Reconstruction Redefined: Classic Craft Meets Microsurgical Innovation.

The authors illustrate a unique case of total nasal reconstruction that successfully combined historical reconstructive techniques with modern microsu...