Surgery

Development and validation of an interpretable machine learning model for postoperative radiotherapy decision-making in ypN0 breast cancer after neoadjuvant chemotherapy: a real-world study.

OBJECTIVE: The subset of breast cancer patients with pathologic node-negative status (ypN0) after neoadjuvant chemotherapy (NAC) who benefit from postoperative radiotherapy (PORT) through a reduced risk of recurrence remains poorly defined. This study aimed to develop and validate an interpretable machine learning (ML) model to perform risk stratification for recurrence among ypN0 patients who all...

Incisional hernia prediction using machine learning models.

BACKGROUND: One of the main complications after laparotomy is incisional hernia (IH), with an incidence of 40% in specific risk groups. There is no consensus on determining which patients are at low or high Risk. There is no currently full peer-reviewed study in which Machine learning (ML) is applied for the prediction of IH, so the objective of this study was to develop a predictive model of IH b...

A Preliminary Report: Screening Idiopathic Scoliosis (IS) With a Smartphone Application.

INTRODUCTION: Idiopathic scoliosis (IS) is a 3-dimensional spinal deformity that affects ∼3.1% of the population. Current strategies for IS screening ...

From scalpel to robot: evolution and outlook of oncologic robotic surgery in Colombia.

INTRODUCTION: Robotic surgery has transformed the management of oncologic pathologies by offering minimally invasive approaches with improved precisio...

Deep Learning Model to Detect Diabetic Retinopathy in 45° Images Using Ground Truth from Ultra-Widefield Imaging.

PURPOSE: To evaluate the performance of a deep learning (DL) model in classifying diabetic retinopathy (DR) severity using fundus images with varying ...

Neuroimaging-Based Deep Learning Applications for Lesion Detection and Predicting the Outcome Following Epilepsy Surgery.

Neuroimaging studies are essential for evaluating patients with drug-resistant focal epilepsy and determining their candidacy for epilepsy surgery. Th...

Computer-Aided Detection-Assisted Colonoscopy Teaches Gaze to Improve Adenoma Detection in First-Year Gastroenterology Fellows.

BACKGROUND AND AIMS: The impact of computer-aided detection (CADe)-assisted colonoscopy on gastroenterology fellow trainees remains incompletely defin...

Adaptive Temporal Mixture of Experts for Predicting Stiffness Metrics from the Ocular Response Analyzer and Identifying Keratoconus: Stiffness Estimates from Ocular Response Analyzer.

PURPOSE: To develop a machine learning-based modeling approach for extracting elastic stiffness estimates from Ocular Response Analyzer (ORA) waveform...

Visualization of Breast Reconstruction Outcomes Using an Artificial Intelligence-Enabled Simulator.

INTRODUCTION: Visual aids that simulate personalized postoperative outcomes following breast reconstruction may facilitate shared decision-making and ...

Exploring key risk factors for loss to follow-up after hospitalization for acute stroke.

BACKGROUND: A significant proportion of stroke patients are lost to follow-up (LTFU) after discharge, which may increase risks of morbidity, mortality...

Current Status and Future Perspective for Bladder Cancer MR Imaging and the Vesical Imaging-Reporting and Data System (VI-RADS) in Japan: Challenges and Solutions.

Bladder cancer carries one of the highest lifetime costs among malignancies, and accurate distinction between non-muscle-invasive and muscle-invasive ...

CystoDS: a multiclass endoscopy image dataset for artificial intelligence-assisted bladder cancer detection.

Cystoscopy is a common endoscopic procedure used for the visual inspection of the lower urinary tract, particularly for the detection and surveillance...

Artificial Intelligence Simplification of English and Spanish Surgical Consent Forms: 1-Size Does Not Fit All.

BACKGROUND: Guidelines recommend patient-facing material be written at or below a 6-9 th-grade reading level; however, surgical consent forms frequent...

From manual parametric to artificial intelligence-based automation: A systematic review of recent advances in endoscopic surgical skills evaluation.

Evaluating surgical skills is critical to surgical training. Numerous methods and scoring scales have recently emerged to assess skills. This study sy...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical awareness, improved imaging, and revised classifica...

A dataset of midpalatal suture maturation stage in cone-beam computed tomography.

In the field of orthodontics, the degree of fusion of the midpalatal suture (MPS) is a crucial factor in determining the most appropriate maxillary ex...

The Clinical Utility of Three-Dimensional Liver Modelling: A Multicenter Survey.

Pre-operative planning for complex liver surgery is constrained by 2D CT/MRI. Digital 3D liver models (3DL-RL) may improve decision-making, but multic...

Development and validation of interpretable multimodal clinical-radiomics models for predicting epileptogenic foci and surgical outcomes in tuberous sclerosis complex: A multicenter study.

Precise localization and resection of epileptogenic (epi) foci from multiple cortical foci determine surgical outcomes in the tuberous sclerosis compl...

Diagnostic Imaging Pathways in Peripheral Artery Disease: A Comparative Review of Duplex Ultrasound Through Computed Tomography Angiography.

Peripheral artery disease (PAD) is a major global health challenge, affecting more than 200 million people worldwide and an estimated 8 to 12 million ...

A systematic review of efforts to predict day of surgery cancellation.

BACKGROUND: Day of surgery cancellation (DOSC) for elective surgery occurs in 18% of elective surgeries worldwide with resultant impacts on patients a...