Surgery

Carotid Imaging: Current Concepts and Advanced Imaging.

Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to luminal stenosis severity. However, stenosis alone fails to capture plaque biology, as features such as intraplaque hemorrhage (IPH), lipid-rich necrotic core, fibrous cap rupture, ulceration, and perivascular inflammation strongly influence vulnerability and clinical outcomes. Advances in imaging have s...

Imaging-based stratification of Claudin 18.2-positive gastric adenocarcinoma using 18F-FDG PET/CT radiomics.

PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 expression in gastric adenocarcinoma (GAC), addressing the limitations of intratumoral heterogeneity and invasiveness associated with endoscopic biopsies. METHODS: This retrospective study enrolled 291 patients with pathologically confirmed GAC who u...

A multimodal predictive model incorporating transcriptomic-guided blood biomarkers and clinical variables for sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) is a major complication in the intensive care unit (ICU), and early risk stratification remains challen...

Trajectories and outcomes in patients with cardiogenic shock receiving heart replacement therapies.

BACKGROUND: Data describing trajectories of cardiogenic shock (CS) patients undergoing heart replacement therapies (HRT) remain limited. We aimed to c...

The CAMUS Initiative: A Multiphase, Multicentre International Collaboration to Redefine Risk Stratification, Reporting, and Grading of Surgical Complications in Urology.

Surgical complications remain a major source of preventable morbidity, mortality, and health care expenditure, but existing frameworks such as the Cla...

Whole-transcriptome sequencing and machine learning detect molecular signatures of endometrial cancer in non-invasive vaginal swabs.

OBJECTIVE: Current tissue-based methods for ruling out endometrial cancer in symptomatic women are highly invasive. We explored whether non-invasive v...

Cost-effectiveness analysis of resective epilepsy surgery in drug-resistant patients: an artificial intelligence data modeling.

BACKGROUND: Resective epilepsy surgery has been proven to reduce the number of seizures and improve quality of life in patients with drug-resistant ep...

Transcranial Doppler ultrasonography in geriatric anesthesia: moving toward personalized brain protection strategies.

The increasing volume of geriatric surgical procedures presents a critical challenge: protecting the aging brain from perioperative complications such...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model. PURPOSE: To develop novel AI software for early ...

Integrated Strategies for Nursing and Rehabilitation in Lung Cancer Patients.

This review delineates the pivotal role of nursing and rehabilitation in perioperative management and chemotherapy support for lung cancer patients, w...

Cleft related facial skeletal surgery: an update.

PURPOSE OF REVIEW: This review provides a comprehensive update on advancements and evolving paradigms in cleft-related facial skeletal surgery. It eva...

Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of postoperative cervical cancer patients.

To develop a context-aware multi-instance learning (TransMIL) model based on whole-slide pathological images and integrate it with clinical parameters...

Building and validating machine learning models to predict appendiceal perforation during conservative treatment of fecalith-associated appendicitis: a 20-algorithm multicenter retrospective analysis.

Fecalith-associated appendicitis presents unique challenges in conservative management due to increased perforation risk. Early identification of pati...

AI Models for Surgical Decision Support in Spontaneous Intracerebral Hemorrhage: A Systematic Review in Relation to Trials and Guidelines.

Artificial intelligence (AI) applications for spontaneous intracerebral hemorrhage (ICH) are rapidly expanding, particularly in perioperative imaging ...

Advances in cataract surgery: is a new era on the horizon?

PURPOSE OF REVIEW: To summarize recent technological, procedural and material advances that are reshaping cataract surgery and to appraise their impli...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...

Development and validation of a machine learning model for predicting 6-month mortality in patients with infective endocarditis.

OBJECTIVE: This study aimed to develop and validate a machine learning (ML)-based model for predicting 6-month all-cause mortality in patients diagnos...

Uncovering Global Trends in Surgical Oncology Trials: Applying Natural Language Processing to ClinicalTrials.gov.

BACKGROUND: Identifying surgical oncology trials within the National Clinical Trial (NCT) database is challenging owing to the absence of medical spec...

Circulating Immune Profiles in ACTH-Dependent Cushing's Syndrome.

OBJECTIVE: ACTH-dependent Cushing's syndrome (CS) causes profound immune dysfunction and severe infections. This study aimed to characterize immune ce...

A hierarchical prompt and prototype learning framework for brain disorder classification.

Accurate diagnosis of brain disorders (BDs) is challenging in clinical practice. Most existing deep learning-based methods perform diagnosis only in a...