Surgery

Deep Learning-Based Prediction System for Surgical Difficulty in Rectal Cancer Patients Using MRI Pelvimetry.

PURPOSE: This study presents a system that automatically predicts the difficulty of laparoscopic total mesorectal excision (TME) using magnetic resonance imaging (MRI) pelvimetry and the clinical characteristics of the patients with rectal cancer, using deep learning (DL) technology and statistical analysis. MATERIALS AND METHODS: Colorectal MRI data were collected from patients with rectal cancer...

Interpretable machine learning and deep learning model for discriminating pheochromocytoma from adrenocortical adenoma based on CT: A multicenter study.

BACKGROUND: Differentiating pheochromocytoma (PHEO) from adrenocortical adenoma (ACA) is vital to avoid intraoperative hypertensive crises or redundant surgeries. PURPOSE: To identify the optimal diagnostic strategy by benchmarking various machine learning (ML) and deep learning (DL) architectures for the preoperative differentiation of PHEO from ACA. METHODS: We retrospectively enrolled 401 patie...

Perceptions of clinicians and patients toward artificial intelligence applications in surgery: A scoping review.

BACKGROUND: Widespread adoption of artificial intelligence into surgical care heavily depends on clinician and patient attitudes, which remain poorly ...

Performance of large language models and clinical decision support in perioperative management of oral anticoagulants.

BACKGROUND: Perioperative anticoagulant management is critical because of the competing risks of ischemia and bleeding. Large language models (LLMs) a...

Machine learning-based prediction model for paresthesia improvement after open carpal tunnel release: a preliminary study.

BACKGROUND: Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy of the hand. While carpal tunnel release surgery generally provides ...

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 cataract surgery, particularly with advanced IOLs....

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 with hip fracture, yet its pathogenesis remains u...

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

BACKGROUND: Artificial intelligence has previously demonstrated the capability to interpret cervical spine imaging. The present study aims to identify...

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 develop an automated, deep learning-based framework to ...

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, and personalized surgical planning, ultimately tr...

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 challenge. Given the involvement of DNA methylation...

[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 treatment of GI cancers is significant due to adva...

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

Use of the Ion Robot in the Diagnosis of Pulmonary Nodules: Fine Needle Aspiration Versus Cryobiopsy.

BACKGROUND: Robotic-assisted bronchoscopy platforms provide an innovative approach to the sampling of pulmonary nodules. As compared to other technolo...

A novel serum metabolite classifier for identifying Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) integrating metabolomics and machine learning.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing global health burden, while reliable non-invasive biom...

Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...

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-small cell lung cancer (NSCLC), influencing both sh...

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. In patients with resectable disease, cytoreductiv...

Impact of Generative AI on Operative Planning in Otolaryngology Residents.

PurposeTo quantify how large language model (LLM) assistance influences otolaryngology residents' operative planning in a simulation-based setting.Met...

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 safety. Current models relying on structural parameters...