Surgery

Goals of Care Transitions following Postoperative Undertriage.

BACKGROUND: This study tests the hypothesis that postoperative undertriage of high-acuity patients t...

Intratumoral and Peritumoral Fat CT‑Based Radiomics for Predicting Recurrence Risk in Non-Muscle-Invasive Bladder Cancer: A Two-Center Study.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) has a high risk of recurrence, and multiple s...

TSMS-SAM2: Multi-scale Temporal Sampling Augmentation and Memory-Splitting Pruning for Promptable Video Object Segmentation and Tracking in Surgical Scenarios.

Promptable video object segmentation and tracking (VOST) has seen significant advances with the emer...

Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach.

BACKGROUND: Changes in opioid prescribing practices have evolved, including perioperative settings. ...

Interpretable machine learning using CT radiomics predicts pathological upgrading after secondary resection in non-muscle-invasive bladder cancer.

BACKGROUND AND PURPOSE: Repeat transurethral resection (ReTUR) is essential for reducing residual an...

Spectral entropy variability of intraoperative electrocorticography predicts outcome after epilepsy surgery in people with focal cortical dysplasia.

OBJECTIVE: Epilepsy surgery in people with focal cortical dysplasia (FCD) requires accurate removal ...

Artificial intelligence analysis of minimally invasive surgery data.

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety c...

Resolution of generalized tonic seizures following focal ablative or resective surgery.

OBJECTIVE: Focal brain lesions may underlie generalized tonic seizures, as seen in Lennox-Gastaut sy...

Machine learning integrating MRI and clinical features predicts early recurrence of hepatocellular carcinoma after resection.

This study aims to construct a robust artificial intelligence (AI) model to predict early recurrence...

Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.

BACKGROUND: Precancerous gastric lesions (PLGC) are a critical stage in gastric cancer progression, ...

Deep learning-based automatic adenoid segmentation and a novel volume-based index for adenoid hypertrophy assessment.

BACKGROUND: Adenoid hypertrophy is a common cause of pediatric obstructive sleep apnea (OSA), which ...

A randomized controlled trial of a WeChat-based artificial intelligence agent for postoperative care in orthopedic patients.

Effective postoperative management in orthopedic surgery is often hindered by challenges such as poo...

AI-driven prediction of completion time and errors in the Advanced Training in Laparoscopic Suturing (ATLAS) needle handling task: One step closer to automated surgical skill assessment.

BACKGROUND: The Advanced Training in Laparoscopic Suturing is a proficiency-based curriculum of 6 st...

Prospective validation and real-time implementation of an automated machine learning postoperative mortality prediction model.

BACKGROUND: Machine learning prediction models require prospective validation to ensure implementati...

Rebuilding the pelvis: advances in robotic-assisted management of complex pelvic fractures.

Complex pelvic fractures are infamously challenging to fix surgically because of their fine anatomy ...

Comparative analysis of machine learning algorithms for predicting stereotactic coordinates of the centromedian nucleus.

OBJECTIVE: Deep brain stimulation (DBS) of the centromedian nucleus (CM) of the thalamus is a promis...

Development of a machine learning model to predict intensive care unit bed demand for adult elective surgical patients at a large United Kingdom National Health Service Trust.

BACKGROUND: Elective surgical admissions form a growing share of demand for ICU beds, a constrained ...

Ethical and Regulatory Considerations for Artificial Intelligence Adoption in Craniofacial Surgery.

Artificial intelligence (AI) continues to enhance surgical care, with growing applications in cranio...

AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull.

Artificial intelligence (AI) is increasingly applied in diagnostic imaging to enhance pattern recogn...

External validation of the IHXGboost-P model to predict incisional hernia after midline laparotomy.

BACKGROUND: Incisional hernia (IH) is a significant complication that occurs after midline laparotom...