Surgery

Predicting sperm retrieval success in salvage testicular sperm extraction: a machine learning perspective.

This multicenter retrospective observational study aimed to identify predictive factors for successful secondary testicular sperm extraction (TESE) using advanced machine learning (ML) models. Data from 503 infertile men who underwent secondary TESE between 2021 and 2024 after a previous unsuccessful attempt were analyzed. Preoperative characteristics and laboratory findings were assessed using te...

Optimizing AI implementation for surgery: recommendations for infrastructure and deployment in the operating room.

Recent years have seen a surge in the development of Artificial Intelligence (AI) technologies to enhance intraoperative decision-making and improve patient safety. Yet, real-world evidence on their implementation remains limited. This study evaluated the impact of AI deployment in the operating room across key implementation domains-usability, cost, and carbon footprint-using cloud and edge-based...

AI-driven qualitative skill assessment in laparoscopic training: a prospective observational study.

Qualitative assessment of surgical skills is central to proficiency-based training but remains difficult to scale due to its reliance on expert evalua...

National trends and comparative outcomes of insulin versus non-insulin therapy in acute ischemic stroke patients treated with mechanical thrombectomy: a retrospective cohort study using the national inpatient sample.

Background diabetes mellitus is prevalent among patients with acute ischemic stroke (AIS). The prognostic significance of long-term insulin treatment ...

Machine learning-based risk prediction model for postoperative acute kidney injury in surgical patients with chronic kidney disease (CKD): development, validation, and SHAP-based explainability.

This study aimed to develop machine learning models to predict postoperative acute kidney injury (AKI) in surgical patients with pre-existing chronic ...

Preliminary machine-learning model with clinical, US, and CEUS features for the diagnosis of thyroid follicular-patterned lesions.

BACKGROUND: Though follicular thyroid carcinoma can be confirmed postoperatively by the histological findings of capsular or vascular invasion, preope...

Limited Femoral Joint-Line Alteration and Preserved Extension Lateral Laxity Enhanced Early Outcomes in restricted kinematic alignment TKA.

BACKGROUND: Restricted kinematic alignment (rKA) total knee arthroplasty (TKA) seeks to restore native alignment while limiting excessive correction. ...

Deep learning Algorithm for Wound assessment after total kNee (DAWN) arthroplasty : a prospective study protocol.

AIMS: This study aims to develop and internally validate an AI approach based on a deep learning (DL) algorithm to classify wound photographs as eithe...

"Ethnic Preferences in African American Rhinoplasty using Artificial Intelligence Morphing and Cadaveric Structural Cartilage Grafts".

BACKGROUND: Many African American patients who undergo rhinoplasty prefer to maintain their ethnic characteristics rather than aim toward Euro-Western...

Elasticity-guided tumor resection: applying biomechanical information to neurosurgical practice.

Tumor stiffness and adhesion are decisive factors in neurosurgical strategy, yet they remain absent from standard planning and navigation. Advances in...

Shaping the Future of Nasal Surgery: A Systematic Review of Preservation Rhinoplasty.

BACKGROUND: Preservation rhinoplasty has transformed nasal surgery by prioritizing structural conservation while achieving aesthetic refinement and fu...

Artificial intelligence-based anatomical recognition improves surgeon decision-making during robotic gastrectomy.

BACKGROUND: Artificial intelligence (AI)-based anatomical recognition has emerged to support intraoperative cognition; however, its clinical utility b...

Genome-wide variation in cell-free DNA end motif entropy predicts immunotherapy response in head and neck cancer.

BACKGROUND: Minimally invasive biomarkers predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinical ...

Composite small vessel disease scores predict hemorrhagic transformation after thrombectomy: a machine learning study.

BACKGROUND: Hemorrhagic transformation (HT) is a major complication of acute ischemic stroke (AIS), especially after mechanical thrombectomy (MT) and ...

Quantum machine learning for predicting anastomotic leak: a clinical study.

Anastomotic leak is a life-threatening complication following colorectal surgery. This study benchmarks Quantum Neural Networks (QNNs) against hyperpa...

A deep learning system for non-invasive breast cancer diagnosis with multimodal data.

Early and accurate diagnosis of breast cancer is critical for minimizing needle biopsies and enhancing patient outcomes and requires effective integra...

Physics-informed DynUNet for brain metastasis segmentation.

BACKGROUND: In neuro-oncology, detecting, segmenting, and delineating the boundaries of small-volume brain metastatic foci remains a significant chall...

Machine Learning-Based Prediction of Long-Term Intraocular Pressure Fluctuations in Open-Angle Glaucoma.

OBJECTIVE: To investigate the predictability of long-term intraocular pressure (IOP) fluctuations in open-angle glaucoma eyes implanted with a telemet...

CT-based 3D planning-supported stem-free screw-cement augmentation versus 2D radiograph-planned short-stem reconstruction for AORI type I-II medial tibial defects in TKA: a two-year retrospective study.

BACKGROUND: Medial tibial defects in varus knee osteoarthritis (KOA) challenge alignment and tibial support in primary total knee arthroplasty (TKA). ...

Application of artificial intelligence-assisted education for postoperative pulmonary rehabilitation: a hybrid model of AI and nurse-driven support.

OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cance...