Academic Articles & Research Papers

Machine learning in keratoconus: severity grading, progression prediction, and surgery outcomes.

Artificial intelligence in Saudi otolaryngology research: a scoping review of the current landscape, gaps, and future directions.

Computer Vision Analysis of Intraoperative Video

OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by comput...

Generalizable stereo depth estimation with masked image modelling

Abstract Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizab...

Computer vision in surgery

Porous Ti6Al4V as an Osteogenic Microenvironment? A Perspective From Architecture-Matched In Vitro Studies.

Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents

Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients

ObjectivesThis study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas.MethodsWe incorporated 32 cases of left insular gliomas and 20 ...

Applications of deep learning in dentistry

Evaluating artificial intelligence for a focal nodular hyperplasia diagnosis using magnetic resonance imaging: preliminary findings

PURPOSE: This study aimed to evaluate the effectiveness of artificial intelligence (AI) in diagnosing focal nodular hyperplasia (FNH) of the liver using magnetic resonance imaging (MRI) and compare its performance with that of radiologists....

Nomogram for Postoperative Permanent Neurologic Dysfunction Following Acute Type A Aortic Dissection Surgery: A Multicentral Retrospective Study.

Modern Burn Surgery: Operative Decisions From Acute Excision to Long-Term Reconstruction.

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

Prediction of lymph node metastasis in papillary thyroid carcinoma using non-contrast CT-based radiomics and deep learning with thyroid lobe segmentation: A dual-center study

Objectives: This study aimed to develop a predictive model for lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) patients by deep learning radiomic (DLRad) and clinical features. Methods: This study included 271 thyroid lobes...

Advanced organ protection strategies in aortic arch surgery: A narrative review.

Correlation analysis between preoperative MRI image features based on image reconstruction algorithms and incision healing in patients with benign hepatobiliary diseases undergoing postoperative drainage tube placement

Objective: This study was designed to examine the association between preoperative abdominal MRI features derived using a deep learning-based reconstruction (DL-Recon) algorithm and postoperative surgical incision-healing outcomes, while ev...

The Outcomes of Combined Approach Sialendoscopy and Multidisciplinary Salivary Gland Society Questionnaire (Q10 version) in Patients with Proximal/Intraglandular Stones of the Submandibular Gland.

CT-based three-dimensional virtual reduction with implant templating for tibial plateau fractures involving the posterolateral region: a retrospective cohort study of early postoperative CT reduction quality.

How reliable is percutaneous transforaminal endoscopic discectomy during the learning curve? A comparison of outcomes with microsurgical discectomy experiences.

Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery

Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...