Surgery

The feasibility and accuracy of real-time intra-operative confocal tissue diagnosis in brain and spine cancer surgery.

Real-time intra-operative brain tumour tissue analysis can reduce turnaround times and enable repeated sampling, enhancing diagnostic accuracy and guiding resection. We investigated the use of an ultra-fast confocal microscopy scanner (Histolog®, SamanTree Medical SA) for real-time brain tumour tissue diagnosis. This study aims to demonstrate Histolog®’s diagnostic accuracy in a cohort of brain or...

Technological advancements for improving preoperative assessment and precision in cardiovascular surgery.

INTRODUCTION: Cardiovascular surgery including cardiac surgery and complex endovascular procedure needs careful preoperative planning as well as intraoperative precision to improve outcomes and ameliorate complications. During the last decades, several technological advancements have been made that could improve preoperative assessment, design of the surgical procedure, risk prediction as well as ...

Application of AI Models for Preventing Surgical Complications: Scoping Review of Clinical Readiness and Barriers to Implementation.

BACKGROUND: The impact of surgical complications is substantial and multifaceted, affecting patients and their families, surgeons, and health care sys...

STRATUM-OS: first step in the development and validation of the STRATUM tool based on multimodal data processing to assist surgery in patients affected by intra-axial brain tumours - observational study protocol.

INTRODUCTION: Integrated digital diagnostics can support complex surgeries in many anatomic sites, and brain tumour surgery represents one of the most...

Assessment and AI-Based Prediction of Complications in Reduction Mammoplasty: A Combined Statistical and Fuzzy Inference Approach in a 10-Year Cohort from Tehran Hospitals (2013-2023).

INTRODUCTION: Gigantomastia causes physical, psychological, and dermatological issues, often with ptosis; reduction mammoplasty effectively relieves s...

Explainable machine learning for risk prediction of acute cardiac tamponade during atrial fibrillation ablation.

Cardiac tamponade is a rare yet catastrophic complication during atrial fibrillation (AF) catheter ablation. Influenced by multiple procedural and pat...

Prediction of Major Stroke (NIHSS > 5) Based on MR Perfusion Imaging Using a 3D ResNet.

PURPOSE: Prediction of stroke symptoms from perfusion patterns in ischemic stroke imaging would be desirable for decision making in relevant clinical ...

AI-Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue.

Colorectal cancer remains one of the leading causes of cancer mortality, and its prognosis is strongly dependent on early detection. Conventional diag...

Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.

PURPOSE: Selective Internal Radiotherapy (SIRT) is an established treatment option for hepatocellular carcinoma (HCC). However, a major complication i...

Justifying model complexity: Evaluating transfer learning against classical models for intraoperative nociception monitoring under anesthesia.

BACKGROUND: Accurate intraoperative detection of nociceptive events is essential for optimizing analgesic administration and improving postoperative o...

AI-driven crown generation: A comparative analysis of point cloud completion models for mandibular first molar restoration.

OBJECTIVES: This study aimed to adapt and evaluate three established artificial intelligence (AI)-driven point cloud completion models-PF-Net, PCN, an...

Computer Vision for Preoperative Soft-Tissue Landmarking in Cleft Lip Repair: A Systematic Review.

BACKGROUND: Cleft lip repair presents complex surgical challenges requiring precise preoperative planning. Emerging computer vision technologies power...

Can ChatGPT Teach Tendon Repair Suturing? A Comparison With Video Instruction in a Simulation-Based Environment: A Pilot Study.

OBJECTIVE: To compare the effectiveness of ChatGPT-guided instruction versus video-based instruction for teaching the Modified Kessler tendon repair t...

Testing the Implementation and Acceptance of Generative Artificial Intelligence to Augment Vascular Surgery Journal Club.

INTRODUCTION: Medical applications of generative artificial intelligence (GAI) have received much attention, however, it remains unclear whether GAI c...

Comparable survival after lobectomy and total thyroidectomy for T3b differentiated thyroid carcinoma: A population-based study.

BACKGROUND: The 2025 American Thyroid Association guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC). However...

Machine learning-based prediction of significant intraoperative blood loss to guide risk-adapted blood management decisions in spinal surgery.

INTRODUCTION: Significant blood loss (≥ 500 mL) during spinal surgery is common and linked to greater transfusion requirements and worse outcomes. Pre...

Large Language Model for Postoperative Clinical Decision Support in a Neurosurgery Ward in the Gambia: A Prospective Pilot Feasibility Study.

BACKGROUND AND OBJECTIVES: Access to specialty surgical care is growing in many low-income countries, but it remains unclear how hospital workforces c...

Artificial Intelligence-Driven Three-Dimensional Reconstruction in Lung Cancer Surgery: Current Status and Future Perspectives.

BACKGROUND: Three-dimensional (3D) reconstruction is an important adjunct in lung cancer surgery for visualizing pulmonary anatomy, supporting preoper...

Predicting the vault after ICL implantation using intraoperative OCT: Establishment and application of models.

PURPOSE: This study aimed to develop a machine learning (ML) model using intraoperative optical coherence tomography (iOCT) data to predict postoperat...

Risk Prediction of Chronic Kidney Disease Progression in Type 2 Diabetes Mellitus Across Diverse Populations.

Chronic kidney disease (CKD) is a common complication of type 2 diabetes mellitus (T2DM), with limited predictive tools for individualized prognosis, ...