Surgery

The Role of AI in Modern Hernia Surgery: A Review and Practical Insights.

BackgroundArtificial intelligence (AI) is revolutionizing various aspects of health care, particularly in the surgical field, where it offers significant potential for improving surgical risk assessment, predictive analytics, and research advancement. Despite the development of numerous AI models in surgery, there remains a notable gap in understanding their specific application within the context...

Development and validation comparison of multiple models for perioperative neurocognitive disorders during hip arthroplasty.

This study aims to develop optimal predictive models for perioperative neurocognitive disorders (PND) in hip arthroplasty patients, thereby advancing clinical practice. Data from all hip arthroplasty patients in the MIMIC-IV database were utilized to predict PND. With 62 variables, we applied multiple logistic regression, artificial neural network (ANN), Naive Bayes, support vector machine, and de...

Predicting postoperative pulmonary infection in elderly patients undergoing major surgery: a study based on logistic regression and machine learning models.

BACKGROUND: Postoperative pulmonary infection (POI) is strongly associated with a poor prognosis and has a high incidence in elderly patients undergoi...

The Performance of Artificial Intelligence in One Anastomosis Gastric Bypass Surgery: Comparative Efficacy of ChatGPT-4.0, ChatGPT-Omni, and Gemini AI.

BACKGROUND: The integration of artificial intelligence (AI) into medical practice opens up new frontiers for decision support, especially in intricate...

Predicting complications after laparoscopic surgery for ureteropelvic junction obstruction using machine learning models: a retrospective cohort study.

PURPOSES: Postoperative complications in patients with ureteropelvic junction obstruction (UPJO) negatively impact surgical outcomes and may necessita...

Systematic review on the use of artificial intelligence to identify anatomical structures during laparoscopic cholecystectomy: a tool towards the future.

PURPOSE: Bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is a dreaded complication. Artificial intelligence (AI) has recently been int...

Machine learning predicts spinal cord stimulation surgery outcomes and reveals novel neural markers for chronic pain.

Spinal cord stimulation (SCS) is a well-accepted therapy for refractory chronic pain. However, predicting responders remain a challenge due to a lack ...

International expert consensus on the current status and future prospects of artificial intelligence in metabolic and bariatric surgery.

Artificial intelligence (AI) is transforming the landscape of medicine, including surgical science and practice. The evolution of AI from rule-based s...

Design and application of ISSA-BP neural network model for predicting soft tissue relaxation force.

: Accurate biomechanical modeling is crucial for enhancing the realism of virtual surgical training. This study addressed the computational cost and c...

Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.

OBJECTIVE: Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervent...

State-of-the-art for automated machine learning predicts outcomes in poor-grade aneurysmal subarachnoid hemorrhage using routinely measured laboratory & radiological parameters: coagulation parameters and liver function as key prognosticators.

The objective of this study was to develop and evaluate automated machine learning (aML) models for predicting short-term (1-month) and medium-term (3...

UC-NeRF: Uncertainty-Aware Conditional Neural Radiance Fields From Endoscopic Sparse Views.

Visualizing surgical scenes is crucial for revealing internal anatomical structures during minimally invasive procedures. Novel View Synthesis is a vi...

Deep Learning for High Speed Optical Coherence Elastography With a Fiber Scanning Endoscope.

Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via clinical imaging systems, e.g., ultrasound or magn...

Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.

Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purpos...

Comprehensive overview of artificial intelligence in surgery: a systematic review and perspectives.

The rapid integration of artificial intelligence (AI) into surgical practice necessitates a comprehensive evaluation of its applications, challenges, ...

A multi model deep net with an explainable AI based framework for diabetic retinopathy segmentation and classification.

Diabetic Retinopathy (DR) is a serious condition affecting diabetes people caused by hemorrhage in the light-sensitive retinal area. DR sufferers shou...

Deep learning and robotics enabled approach for audio based emotional pragmatics deficits identification in social communication disorders.

The aim of this study is to develop Deep Learning (DL) enabled robotic systems to identify audio-based emotional pragmatics deficits in individuals wi...

A brief history and clinical use of robotic procedures in the cardiovascular system.

Robotic-assisted percutaneous coronary intervention (r-PCI) exemplifies the advancement of interventional cardiology by integrating robotics to improv...

A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization.

Real-time endoscopic rectal lesion characterization employing artificial intelligence (AI) and near-infrared (NIR) imaging of the fluorescence perfusi...

Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.

BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical d...