Surgery

Development and validation of a computational histology artificial intelligence-powered prognostic biomarker in muscle-invasive bladder cancer.

BACKGROUND: Patients with muscle-invasive bladder cancer (MIBC) have heterogeneous outcomes following transurethral resection of bladder tumor (TURBT). We used a computational histopathology artificial intelligence (CHAI)-based platform to develop and validate a digital image-only MIBC prognostic biomarker. METHODS: The CHAI platform extracts histologic features from pre-treatment TURBT specimen H...

TempoSafe-CVS: A Temporal Multi-scale Deep Learning Framework for Automated Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy.

Accurate assessment of the critical view of safety (CVS) is essential for preventing bile duct injuries during laparoscopic cholecystectomy. Existing artificial intelligence approaches primarily rely on static frame-level analysis and often fail to capture the temporal evolution of surgical scenes, limiting their ability to provide reliable and context-aware safety assessment. To address this chal...

Distinct recovery phenotypes after hip arthroscopy reveal dissociation between daily function and sports performance.

BACKGROUND: Hip arthroscopy outcomes for femoroacetabular impingement remain heterogeneous. The Hip Outcome Score (HOS) comprises 2 distinct subscales...

Digital twin-enabled robotic surgery: a bibliometric and knowledge-mapping analysis from patient-specific simulation to autonomy and clinical translation.

Digital twin-enabled robotic surgery is emerging at the intersection of surgical robotics, patient-specific simulation, artificial intelligence, exten...

Machine Learning Characterization of Readmissions After Chronic Subdural Hematoma Hospitalizations.

BACKGROUND AND OBJECTIVES: Readmission after chronic or subacute subdural hematoma (cSDH/sSDH) hospitalization is common, yet clinical attention and t...

Development and validation of natural language processing pipelines to extract injury and surgery-related data elements from ACL reconstruction operative reports.

BACKGROUND: Over 100,000 patients undergo ACLR each year in the United States, providing rich electronic medical record data to improve outcomes, but ...

Local recurrence in rectal cancer: from detection to structured reporting.

Despite advances in total mesorectal excision and neoadjuvant therapy, locally recurrent rectal cancer remains a clinically important source of pelvic...

Correction to: Angioarchitectural features of hemorrhagic presentation of brain arteriovenous malformations: A multivariate and explainable machine learning study.

American College of Surgeons NSQIP Hospital Benchmarking Using Bayesian Variational Inference to Adjust for Many CPT Codes.

BACKGROUND: Current ACS NSQIP benchmarking relies primarily on the principal Current Procedural Terminology (CPT) code for procedure-related risk adju...

An interpretable multimodal biomechanical-radiological model for predicting fixation failure in osteoporotic hip fractures: A retrospective cohort study.

This study aimed to develop and validate a multimodal prediction model integrating biomechanical and radiological variables to predict internal fixati...

Risk analysis and warning model of post-noncardiac surgery acute kidney injury: A retrospective observational study.

Postoperative acute kidney injury (PO-AKI) following noncardiac surgery remains a major clinical challenge, for which effective early warning models a...

New Perspectives on Prosthetically Guided Implant Placement Using Robotic-Assisted Surgery: A Case Report.

PURPOSE: To describe a new clinical protocol for prosthetically guided implant placement with the assistance of a robotic system. MATERIALS AND METHOD...

Effectiveness of Socially Assistive Robots in Promoting Positive Emotional Responses and Alleviating Postoperative Pain Among Children: Quantitative Study.

BACKGROUND: Pain remains a critical issue among hospitalized children and may negatively affect postoperative recovery. In addition to pharmacological...

Machine Learning to Identify Point-of-Care Ultrasound and Evaluate Standardized Documentation: Retrospective Operational Cohort Study.

BACKGROUND: Point-of-care ultrasound (POCUS) is integral to obstetrics and gynecology (OBGYN), offering bedside diagnostic and therapeutic advantages....

Multi-modal AI-enabled steatotic liver disease diagnostics using facial images and metabolomics.

Steatotic liver disease (SLD) affects one-third of the global population, yet current non-invasive diagnostic methods are too costly or operator-depen...

Machine-learning-based source localization for an intraoperative forceps-type positron emission counter.

Intraoperative identification of metastatic lymph nodes in esophageal cancer surgery could enable more selective lymph-node dissection. A forceps-type...

Genome-Wide Association, Polygenic Risk Scores, and Machine Learning for Chronic Post-Surgical Pain Risk Stratification: A UK Biobank Study.

Chronic post-surgical pain is a prevalent and debilitating complication following surgery, representing a clinical challenge. Despite the established ...

Automated CT Volumetry of Peripancreatic Collections for Risk Stratification in Acute Pancreatitis: A Multicenter Retrospective Study.

RATIONALE AND OBJECTIVES: Extrapancreatic necrosis volume is an established prognostic marker in acute necrotizing pancreatitis, yet early diagnosis r...

Urinary volatilomics using liquid-liquid extraction and gas chromatography-mass spectrometry (GC-MS) combined with machine learning algorithms as a tool for diagnosis and surveillance of urothelial bladder cancer.

BACKGROUND: Bladder cancer is the 11th most common cancer in the United Kingdom, with approximately 10,500 new cases annually. Diagnosis and surveilla...

Explainable Deep Learning for Automated Classification of Skeletal and Tumor Pathologies in 3D Volumetric Medical Imaging.

Accurate identification and classification of 3D mesh data in medical imaging are crucial for various clinical and research applications, including su...