Surgery

Development of machine learning-based predictive models for seroma formation after transabdominal preperitoneal inguinal hernia repair.

BACKGROUND: Inguinal hernia repair, particularly transabdominal preperitoneal (TAPP) repair, is a common surgical procedure. However, seroma formation remains a frequent postoperative complication, impacting patient recovery and increasing healthcare burden. Accurate prediction of seroma formation is crucial for personalized patient management and improved outcomes. OBJECTIVE: This study aimed to ...

Trust, truth and transparency: analysing the references underpinning AI-generated surgical information.

INTRODUCTION: Artificial intelligence (AI) chatbots, powered by large language models, are used increasingly for disseminating surgical information, but concerns about accuracy, hallucinations and source reliability persist. This study evaluates the sources of information upon which these systems rely when producing medical information. As these models generate language without true comprehension ...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable m...

Development and Validation of a Machine Learning Model for Incident Heart Failure Prediction in Chronic Kidney Disease: A Multicenter Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) and heart failure (HF) share pathophysiological mechanisms, rendering HF one of the most burdensome cardiovas...

Artificial intelligence and capsule endoscopy.

The advent of artificial intelligence (AI) is revolutionizing today's clinical practice, particularly in gastroenterology, where capsule endoscopy (CE...

Al-enhanced Dynamic Virtual Patient Workflow for Full-arch Implant Rehabilitation.

Accurately recording implant positions and maxillomandibular relationships in completely edentulous patients for the fabrication of fixed implant-supp...

Practical adaptability of a pre-hospital prognostic prediction model for patients following out-of-hospital cardiac arrest during the COVID-19 pandemic.

OBJECTIVES: The overwhelmed situation under the COVID-19 pandemic has worsened the quality of emergency medical care and the mortality rate due to out...

Telehealth Approaches for Pediatric Otitis Media and Clinical Outcomes: Scoping Review.

BACKGROUND: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, w...

Representation learning for the prediction of length of stay in infants with congenital heart diseases undergoing cardiac surgery.

AIMS: Congenital heart disease is the most common birth defect and significantly impacts health, mortality, and healthcare costs. Accurately estimatin...

High-Speed Instance Segmentation for Endoscopic Spine Surgery: Multicenter Validation and Inference Speed Evaluation.

Study DesignRetrospective Multicenter Cohort Study.ObjectivesTo develop and validate an AI-based high-speed multi-class instance segmentation system f...

AI-enhanced precision: boosting pathologist confidence in HER2 ultra-low diagnosis through intelligent re-screening.

Accurate assessment of Human Epidermal Growth Factor Receptor 2 (HER2) immunohistochemistry (IHC) expression, particularly the precise identification ...

Enhancing the functionality of soft continuum robots for minimally invasive and endoluminal interventions: a review.

The introduction and development of soft continuum robots (SCRs) for minimally invasive surgery and endoluminal intervention offers a promising option...

Influencing factors and predictive model for in-hospital complications in patients with spontaneous intracerebral hemorrhage: A single-center retrospective study.

Diagnostic performance and confidence of an optimized deep-learning algorithm for the detection of intracranial hemorrhages.

OBJECTIVES: To evaluate the performance of an optimized deep-learning-based algorithm (AI) for the detection and subtyping of intracranial hemorrhage ...

A decade-long shift in use of energy devices for BABA robotic thyroidectomy: automated video analysis by deep learning.

Bilateral axillo-breast approach robotic thyroidectomy (BABA RT) is a well-established minimally invasive surgical option; however, shifts in preferen...

Distillation-SAM: Knowledge Distillation Based Auto-prompt Embedding Learning for Surgical Image Segmentation.

Surgical image segmentation is vital for various stages of surgical procedures, from preoperative planning to real-time navigation and postoperative a...

Mandibular Distraction Osteogenesis as Paradigm Shift for Treatment of Tongue-Based Obstructive Apnea: Results of a 16-Year, Hospital-Wide Intervention Trial.

BACKGROUND: Mandibular distraction osteogenesis (MDO) has emerged as the preferred surgical treatment for neonatal tongue-based airway obstruction (TB...

Minimally invasive spine surgery: current advantages, limitations, and future directions.

Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided n...

Adiposome Lipidomic Shifts Following Bariatric Surgery in Association With Weight Loss and Cardiometabolic Benefit.

CONTEXT: Adiposomes carry bioactive lipids that shape systemic metabolism and vascular function. OBJECTIVE: Building on our previous findings that obe...

Accuracy of Diagnosis and Anticipation of Future Treatment in Pediatric Peripelvic Infections: The Role of Multisurgeon Review and Implications for Future Machine Learning Algorithms.

INTRODUCTION: MRI is commonly used to evaluate pelvic musculoskeletal infections. Limited "quick" MRI protocols enable timely imaging without intraven...