Surgery

Enhancing Privacy-Preserving Deployable Large Language Models for Perioperative Complication Detection: A Targeted Strategy with LoRA Fine-tuning

Perioperative complications represent a major global health concern affecting millions of surgical patients annually, yet manual detection methods suffer from significant under-reporting (27%) and misclassification rates. Clinical deployment of large language models (LLMs) for automated complication detection faces substantial barriers including data sovereignty concerns, computational costs, and ...

Revealing the Infiltration: Prognostic Value of Automated Segmentation of Non-Contrast-Enhancing Tumor in Glioblastoma

Precise delineation of non-contrast-enhancing tumor (nCET) in glioblastoma (GB) is critical for maximal safe resection, yet routine imaging cannot reliably separate infiltrative tumor from vasogenic edema. The aim of this study was to develop and validate an automated method to identify nCET and assess its prognostic value. Pre-operative T2-weighted and FLAIR MRI from 940 patients with newly diagn...

Global Research Trends, Hotspots, Impacts, and Emerging Developments in Intelligent Operating Room Nursing: A 10-Year Bibliometric Analysis

The integration of intelligent technologies in operating room nursing represents a rapidly evolving field requiring systematic analysis to understand ...

Clinical-grade autonomous cytopathology via whole-slide edge tomography

Cytopathology plays a central role in the early detection of cancers such as cervical, lung, and bladder cancer due to its speed, simplicity, and mini...

CEREBLEED: Automated quantification and severity scoring of intracranial hemorrhage on non-contrast CT

Intracranial hemorrhage (ICH), whether spontaneous or traumatic, is a neurological emergency with high morbidity and mortality. Accurate assessment of...

Leveraging Machine Learning for Developing and Validating a Neonatal Acute Kidney Injury Prediction Model (NEPHRO): A Comprehensive Evidence-Based Neonatal AKI Risk Stratification Tool

Acute kidney injury (AKI) is a serious and common complication among critically ill neonates. Preventing or treating AKI early requires timely predict...

Prompt injection attacks on vision-language models for surgical decision support

Artificial Intelligence-driven analysis of laparoscopic video holds potential to increase the safety and precision of minimally invasive surgery. Visi...

Justifying model complexity: evaluating transfer learning against classical models for intraoperative nociception monitoring under anesthesia

Accurate intraoperative detection of nociceptive events is essential for optimizing analgesic administration and improving postoperative outcomes. Whi...

Joint associations of device-measured physical activity and sleep duration with incident major adverse cardiovascular events: prospective analysis of the UK Biobank

The interaction between physical activity and sleep with cardiovascular disease remains poorly understood, despite both being key risk factors. This s...

Artificial Intelligence for Surgical Scene Understanding: A Systematic Review and Reporting Quality Meta-Analysis

Surgical scene understanding (SSU) describes the use of Artificial Intelligence (AI) to provide an understanding of visual components of surgical imag...

Patient-Specific and Interpretable Deep Brain Stimulation Optimisation Using MRI and Clinical Review Data

Optimisation of Deep Brain Stimulation (DBS) settings is a key aspect in achieving clinical efficacy in movement disorders, such as the Parkinson’s di...

White matter characterization in regions of edema surrounding meningioma brain tumor using diffusion MRI

White matter (WM) tract detection is critical in presurgical planning of tumor resection however, standard-of-care imaging techniques including T1-wei...

Multilevel predictors categorization for post-CABG atrial fibrillation prediction

Postoperative atrial fibrillation (PoAF) is known as common coronary artery bypass grafting (CABG) complication. Despite its association with increase...

External Validation of a Machine Learning Model to Predict Postpartum Hemorrhage in a US Northeastern Healthcare System

Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction may prevent adverse maternal outcomes, and efforts...

Predicting Near-term Mortality in Heart Failure: External Validation of Electronic Health Record-Based Deep Learning Model

The dire consequences of heart failure (HF) patient non-response to guideline directed medical therapy often fuel early, non-selective referral for su...

Incidence, Outcomes and Risk Factors of Cardiac Arrest Among Surgical Patients in the UK Biobank: A Population-Based Cohort Study

Perioperative cardiac arrest (CA) is a devastating surgical complication, yet its epidemiology and risk factors across diverse surgical populations ar...

Large Language Models for Zero-Shot Procedure Extraction in Orthopedic Surgery: A Comparative Evaluation

Operative notes in electronic health records contain critical information for understanding surgical care, yet manual coding is time-consuming, costly...

From Evidence to Data Framework: Decision Factors and Structured Data for AI-Driven Clinical Decision Support Systems in Offloading Footwear

Diabetes-related foot ulcers (DFUs) are a serious complication of diabetes, often resulting in infection, amputation, or even mortality. Offloading fo...

Surgical Information Assistant: an agentic information retrieval system for surgical information and a benchmark dataset

We present the Surgical Information Assistant, an agentic retrieval-augmented generation (RAG) system designed to improve access to surgical knowledge...

Surgical Procedure Recognition Using Quantum Machine Learning

Surgical procedure recognition is the process of identifying tasks and gestures done during a surgical process and is a field that has been widely res...