Surgery

Automated Melanocytic Lesion Classification: Capsule Networks Trained With Synthetic Images Can Outperform Networks Trained With Real Images.

BACKGROUND/OBJECTIVES: Convolutional neural networks (CNNs) are known, due to inherent flaws in their design, to be subject to classification error. Many of these shortcomings in classification performance were addressed in 2017 with the introduction of capsule networks (CNs). The objective of this investigation is to determine the classification performance of a CN with respect to dermoscopic ima...

Transcatheter aortic valve implantation for symptomatic severe aortic stenosis and its expanding clinical indications.

Transcatheter aortic valve implantation (TAVI) is a minimally invasive treatment for symptomatic severe aortic stenosis (AS) that was initially developed for patients with prohibitive surgical risk. Since the first-in-human procedure in 2002, TAVI has gained global acceptance owing to its favorable clinical outcomes and faster recovery than those associated with surgical aortic valve replacement. ...

Label-free saliva screening platform using M13 bacteriophage-based 3D plasmonic structures for MRONJ diagnosis.

Medication-related osteonecrosis of the jaw (MRONJ) is a severe complication associated with antiresorptive or antiangiogenic agents, often leading to...

Protocol for the development and validation of a questionnaire to evaluate user-robot interaction in the compounding of hazardous drugs in a hospital setting.

INTRODUCTION: The automation of hazardous drug preparation in hospitals using robotic systems is an effective strategy to enhance safety, quality, and...

End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study.

BACKGROUND: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet ...

Machine Learning Integration of MRI Intratumoral and Peritumoral Radiomics Features for Predicting PNSTs Postoperative Complications.

RATIONALE AND OBJECTIVES: Postoperative complications (15-76%) substantially affect patients with peripheral nerve sheath tumors (PNSTs), yet objectiv...

Ethical and legal challenges of integrating artificial intelligence into paediatric surgery.

INTRODUCTION: Artificial intelligence (AI) technologies are increasingly being trialled with applications spanning imaging, robotic assistance and ear...

Deep learning pipeline for trapezium segmentation in thumb radiographs.

OBJECTIVE: Accurate identification of the trapezium is crucial for trapeziometacarpal (TMC) arthroplasty but remains challenging on standard radiograp...

Navigated hepatic tumor resection using intraoperative ultrasound imaging.

PURPOSE: This proof-of-concept study evaluates the feasibility and accuracy of an ultrasound-based navigation system for open liver surgery. Unlike mo...

The Predictive Value of Machine Learning for Postoperative Delirium in Cardiac Surgery: Systematic Review and Meta-Analysis.

BACKGROUND: Postoperative delirium (POD) following cardiac surgery is a severe complication, and early identification of delirium risk remains a chall...

Real-time intraoperative confocal laser endomicroscopy with on-site neuropathologist consultation for glioma margin assessment: illustrative case.

BACKGROUND: Achieving maximal safe resection in glioma surgery requires accurate real-time margin assessment, yet existing technologies have limitatio...

Predicting Geriatric Rehabilitation Stays of ≤4 Weeks After Hip Fracture Surgery: Machine Learning Approach Using Physical Activity and Patient Data.

BACKGROUND: In 2022, over 18,000 patients aged ≥70 years were hospitalized in the Netherlands for a hip fracture, with 50% requiring geriatric rehabil...

Retinal vascular alteration following surgical intraocular pressure reduction in primary angle closure disease.

AIMS: To investigate retinal vascular geometric alterations following intraocular pressure (IOP)-lowering surgery in patients with primary angle closu...

Large language model and Gd-EOB-DTPA-enhanced MRI-based risk stratification system for postoperative hepatocellular carcinoma: a multicenter study.

OBJECTIVE: To develop and validate a Fully Automated Stratification System (FASS) integrating serum biomarkers, automated radiomic features, and large...

Development of an automatic segmentation system for anterolateral thigh flap perforators in maxillofacial reconstruction.

The anterior thigh (ALT) flap is commonly used in reconstructive surgery, especially in maxillary reconstruction. Accurately identifying the perforato...

Hyperspectral imaging for intraoperative brain tumor identification through fusion of spectral, textural, and spectral index features.

Brain tumor is a common neurological surgical disease, where surgical resection is the primary treatment method. Neurosurgeons need to accurately dete...

Holding the Scalpel: Scientific Authorship and Responsibility in the Era of Generative Artificial Intelligence.

Scientific writing and authorship are fundamentally acts of professional judgment and responsibility. This essay examines these principles in the era ...

Parietal repetitive transcranial magnetic stimulation enhances functional connectivity in patients with minimally conscious state.

The basis of disorders of consciousness is the destruction of brain functional connectivity, and the restoration of damaged connectivity is considered...

MRI-based deep learning and radiomics for preoperative prediction of P53abn endometrial cancer: A multicenter study.

PURPOSE: To develop and validate a non-invasive magnetic resonance imaging (MRI)-based deep learning and radiomics approach for the preoperative diffe...

Machine learning-based prediction and quantification of OCD surgery and pedigree effects on racehorse performance.

Osteochondritis dissecans (OCD) is a common developmental orthopedic condition in Thoroughbred racehorses and although arthroscopic surgery is widely ...