Surgery

Prediction of Postoperative Vomiting Within 24 Hours Using Machine Learning With Large Language Model-Enhanced Interpretability: Development and Validation Study.

BACKGROUND: Postoperative nausea and vomiting are common complications after anesthesia. However, vomiting represents a clinically distinct and objectively measurable endpoint. OBJECTIVE: This study aimed to develop and internally validate predictive models for postoperative vomiting within 24 hours using structured perioperative data and unstructured clinical text, while introducing a structured ...

Artificial intelligence in medicine: a clinician-oriented guide and operational framework to evaluate new AI devices.

BACKGROUND: Artificial Intelligence (AI) is rapidly transitioning from experimental research to daily medical practice, yet the medical community's understanding of these tools remains largely confined to visible 'front-end' applications with which the clinician can directly interact (such as decision support systems and conversational agents). This perspective overlooks the proliferation of 'back...

Incomplete Reporting Persists in Orthopedic Machine Learning Models: A Systematic Review of TRIPOD and TRIPOD+AI Reporting Completeness.

BACKGROUND AND OBJECTIVE: Machine learning (ML) prognostic models in orthopedic surgery are published at an accelerating pace, yet whether reporting m...

Exploring patient and NHS staff acceptability of artificial intelligence-supported surgical wound monitoring within the WISDOM feasibility study: a multi-centre qualitative interview study.

OBJECTIVE: Artificial intelligence (AI) is beginning to be used within digital surgical wound monitoring to facilitate implementation at scale. AI acc...

Preoperative electrocardiography for predicting cardiovascular events after noncardiac surgery: a secondary analysis of two prospective cohorts.

BACKGROUND: The predictive value of preoperative resting ECGs for cardiovascular events after noncardiac surgery is unclear. This study evaluated whet...

Development and external validation of a machine learning model for predicting postoperative hydrocephalus in 1,073 posterior fossa tumor patients.

Postoperative hydrocephalus is a common complication following posterior fossa tumor resection, affecting 7-40% of patients. Although preoperative cer...

Era-specific prognostic factors and an interpretable machine-learning survival model for renal cell carcinoma brain metastases.

BACKGROUND: Brain metastases (BM) in renal cell carcinoma (RCC) are associated with poor prognosis and limited clinical guidance. We aimed to identify...

Large language models as sources of patient information on robotic knee arthroplasty: a comparative evaluation.

BACKGROUND: Robotic-assisted total knee arthroplasty (rTKA) is increasingly used because of its surgical precision. However, inconsistent outcomes and...

[Research and application of artificial intelligence in tooth extraction].

Tooth extraction is a common procedure in oral clinical practice. However, imaging interpretation, risk assessment, and perioperative management remai...

Large Language Models Improve Operative Note Coding Accuracy and Financial Outcomes in Neurotology.

OBJECTIVE: To compare coding accuracy and financial impact between an institution's large language model (LLM) and centralized human coders for neurot...

Causal treatment effects of gait-analysis-informed surgery on the Gait Outcomes Assessment List in children with cerebral palsy.

AIM: To estimate the effect of surgery on parent-reported gait outcomes as measured using the Gait Outcomes Assessment List (GOAL) questionnaire in a ...

Development of a machine learning-based noninvasive diagnostic model for liver fibrosis in metabolic-associated steatotic liver disease.

BACKGROUND: To address the lack of simple tools for assessing fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD), this study...

Prediction of postoperative acute kidney injury in patients undergoing off-pump coronary artery bypass grafting: A machine learning model.

BACKGROUND: The incidence of cardiac surgery-associated acute kidney injury (CSA-AKI) is 26.0%-28.5%. Among cardiac procedures, off-pump coronary arte...

Intracranial pressure physiology, monitoring and individualized management in the acute brain injured patient.

Acute brain injury (ABI), including traumatic brain injury, ischemic and hemorrhagic stroke, is associated with high morbidity and mortality, which is...

Artificial Intelligence-Driven Video-Based Surgical Skill Assessment in Hepatobiliary Laparoscopic Surgery.

The use of artificial intelligence to predict postoperative outcomes following percutaneous nephrolithotomy: A systematic review of prognostic modeling studies.

Artificial intelligence (AI) is increasingly applied in clinical practice to enhance prediction of postoperative outcomes. This systematic review eval...

Performance of 5 Large Language Models in Perioperative Consultation for Pediatric Hypospadias: Cross-Sectional Comparative Study.

BACKGROUND: Hypospadias is a common congenital malformation requiring surgery. Caregivers face substantial perioperative information needs, and large ...

End-to-End Clinical Validation of a Human-Supervised Large Language Model Agent for Enterprise Surgical Pathology Reporting.

Large language models (LLMs) show promise for text-based pathology tasks, yet most reported applications remain experimental, lack formal clinical val...

Towards Explainability in Deep Learning for Detection of Five Major Intracranial Hemorrhage Subtypes on Head CT Using Multi-window DICOM Imaging and Patient-Level Cross-Validation.

Intracranial hemorrhage (ICH) is a time-critical neurologic emergency where delayed diagnosis can worsen outcomes. Non-contrast head CT is the first-l...

Early Prediction of External Ventricular Drain Weaning Trial Outcome in Patients with SAH Based on ICP Pulse Morphological Similarity: A Single-Center Retrospective Cohort Analysis.

BACKGROUND: External ventricular drain (EVD) weaning trials assess the ability of patients with nontraumatic subarachnoid hemorrhage (SAH) to maintain...