Surgery

Predicting Postoperative Anterior Chamber Depth, Intraocular Lens Tilt, and Decentration Using an Internally Validated Machine Learning Model.

INTRODUCTION: Precise intraocular lens (IOL) positioning is critical for optimal visual outcomes in ...

Integrated High-Throughput Targeted Metabolomics and Machine Learning for Early Prediction and Prevention of Postoperative Delirium in Older Adult Surgical Patients: Prospective Multicenter Cohort Study.

BACKGROUND: Postoperative delirium (POD) is a common and severe complication in older adult patients...

Deep Learning-Based Identification of Surgical Candidacy for Cervical Spinal Cord Decompression.

BACKGROUND: Artificial intelligence has previously demonstrated the capability to interpret cervical...

Deep-learning based quantitative evaluation of postoperative atelectasis following right upper lobectomy.

Existing methods of grading atelectasis are typically subjective and not scalable. We aimed to devel...

Empowering surgeons with integrated synthetic data: solutions for mastering complex clinical scenarios.

Synthetic data generation across domains can bridge gaps between visual training, skill development,...

Peripheral blood mononuclear cell DNA methylation signatures guide surgical decision-making in indeterminate pulmonary nodules.

BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical c...

[Current applications and prospects of artificial intelligence in perioperative comprehensive management for gastrointestinal surgery].

The shift from the traditional empirical approach to a more data-driven method in the diagnosis and ...

Unsupervised clustering analysis reveals distinct postoperative cortisol trajectories following pituitary adenoma resection in Cushing's disease.

Artificial intelligence-assisted risk prediction of postoperative pulmonary complications in non-small cell lung cancer surgery.

BACKGROUND: Pulmonary complications are the most frequent adverse events following surgery for non-s...

The Negative Impact of a Non-Therapeutic Laparotomy in Patients With Inoperable Colorectal Peritoneal Metastases.

BACKGROUND: The peritoneum is the third most prevalent location for metastases of colorectal cancer....

Impact of Generative AI on Operative Planning in Otolaryngology Residents.

PurposeTo quantify how large language model (LLM) assistance influences otolaryngology residents' op...

Perioperative hypoxaemia early warning based on high-frequency waveform fusion and deep learning.

The accurate prediction of impending intraoperative hypoxaemic events is paramount for patient safet...

Comparing manual and automated methods for extracting perihematomal features in predicting hemorrhage expansion in deep intracerebral hemorrhage.

Digital twins in urological oncology and surgery: A review of emerging applications.

BACKGROUND: Digital twin technology represents a transformative approach in healthcare, creating vir...

AI-driven Predictive Models in Endourological Treatment of Urolithiasis: A Systematic Review of Nomogram Applications from EAU Endourology.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical ...

Predicting intracranial aneurysm rupture risk and intervention outcomes using denoising-enhanced CT Angiography.

BACKGROUND AND PURPOSE: To develop a comprehensive multi-modal framework for assessing the rupture r...

Pfirrmann Grading and Features of Internal Derangement Identified in Discs Studied By Lumbar Discography in Patients with Chronic Low Back Pain.

BACKGROUND AND PURPOSE: Lumbar disc degeneration Pfirrmann Grade (PfGr) is commonly used to evaluate...

Post-operative delirium risk estimation and assessment with machine learning: development and validation of the Open-DREAM Model: A peri-operative dataset analysis.

BACKGROUND: Postoperative delirium (POD) is a common and serious complication in older surgical pati...

Evaluation of an AI-Driven Risk Stratification System for Clinical Deterioration in Geriatric Hip Fracture Patients.

OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI...

"Do as I say and not as I do: Surgical critical care program directors shape the future" authors' response to the Letter to the Editor entitled: "Artificial intelligence literacy and infectious diseases competency: Essential considerations for future revisions of the surgical critical care curriculum".

Machine Learning-Based Risk Stratification for Symptomatic Intracranial Hemorrhage and 3-month Prognosis Following Intravenous Thrombolysis.

INTRODUCTION: Intravenous thrombolysis (IVT) with tissue-type plasminogen activator (tPA) is a corne...