Surgery

[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.

Functional evaluation in adult spinal deformity can be reduced to 3 key kinematic parameters that can sufficiently predict health-related quality of life outcomes: an observational prospective study.

BACKGROUND CONTEXT: Recently, functional evaluation using 3D gait analysis (3DGA) proved to predict ...

Anatomy data driven mechanical adaptation of bone tunnel-screw interface in ACL reconstruction.

PURPOSE: Anatomical information about bone microstructure at the anterior cruciate ligament attachme...

Are machine learning models superior to logistic regression models to predict 30-day mortality post-hip fracture surgery?

Hip fractures represent a significant global health burden, with high mortality rates. Accurate pred...

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 ...

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...

Predicting Pediatric Urological Surgery Duration Through Multimodal Patient-Physician Feature Fusion: Deep Learning Framework Incorporating Clinical Text Embedding.

BACKGROUND: Accurate prediction of surgical duration is critical for optimizing operating room sched...

Development of a risk prediction model for second primary thyroid cancer in female breast cancer patients based on machine learning algorithms.

Female breast cancer patients remain at risk of developing additional primary cancers even following...

Future Directions: Artificial Intelligence and Digital Tools in Bladder Cancer Care.

This comprehensive review examines using artificial intelligence (AI) across the diagnostic, therape...

Personalizing anesthetic management in trauma patients using machine learning.

PURPOSE OF THE REVIEW: Artificial intelligence in health is evolving rapidly, and there is a lot of ...