Surgery

Artificial intelligence-based automated surgical workflow recognition in esophageal endoscopic submucosal dissection: an international multicenter study (with video).

BACKGROUND: Endoscopic submucosal dissection (ESD) is a crucial yet challenging multi-phase procedure for treating early gastrointestinal cancers. This study developed an artificial intelligence (AI)-based automated surgical workflow recognition model for esophageal ESD and proposed an innovative training program based on esophageal ESD videos with or without AI labels to evaluate its effectivenes...

Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identify the most important predictors of extubation failure in patients undergoing cardiac surgery. Data from 776 adult patients who underwent cardiac surge...

Ensemble-Based Model-Agnostic Meta-Learning with Operational Grouping for Intelligent Sensory Systems.

Model-agnostic meta-learning (MAML), coupled with digital twins, is transformative for predictive maintenance (PdM), especially in robotic arms in ass...

Contrast-Induced Acute Kidney Injury in Lower Limb Percutaneous Transluminal Angioplasty: A Machine Learning Approach for Preoperative Risk Prediction.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common complication of lower limb percutaneous transluminal angioplasty (PTA). Common r...

The Role of Claude 3.5 Sonet and ChatGPT-4 in Posterior Cervical Fusion Patient Guidance.

BACKGROUND: This study evaluates the role of ChatGPT-4 and Claude 3.5 Sonet in postoperative management for patients undergoing posterior cervical fus...

Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors.

BACKGROUND: Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative ...

Comparing neural language models for medical concept representation and patient trajectory prediction.

Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise...

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.

Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive cor...

Soft robotic hand with tactile palm-finger coordination.

Soft robotic hands with integrated sensing capabilities hold great potential for interactive operations. Previous work has typically focused on integr...

Development of a deep learning-based model for guiding a dissection during robotic breast surgery.

BACKGROUND: Traditional surgical education is based on observation and assistance in surgical practice. Recently introduced deep learning (DL) techniq...

Rapid Blood Clot Removal via Remote Delamination and Magnetization of Clot Debris.

Micro/nano-scale robotic devices are emerging as a cutting-edge approach for precision intravascular therapies, offering the potential for highly targ...

Outcomes of lateral femoral cutaneous nerve decompression surgery in meralgia paraesthetica: assessment of pain, sensory deficits, and quality of life.

PURPOSE: Meralgia paraesthetica (MP) is a rare neuropathy of the lateral femoral cutaneous nerve (LFCN), characterized by thigh pain, paraesthesia, or...

Systematic review on visual aid technologies for surgical assistant robotic devices.

This review comprehensively analyzes the modern literature on including visual aids in diverse surgical assistant robotic systems. The review consider...

Classification method for nailfold capillary images using an optimized sugeno fuzzy ensemble of convolutional neural networks.

This study developed a novel binary classification method for analyzing nailfold capillary images associated with the risk of developing sclerosis. Th...

Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.

Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary ...

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke part...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy....

Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.

BACKGROUND: This study was conducted to assess the association between lifestyle risk factors (LRF) and odds of binge eating disorder (BED) 2 years po...

Assessing operative variability in robot-assisted radical prostatectomy (RARP) through AI.

Robotic-assisted radical prostatectomy (RARP) is the most commonly performed robotic procedure in urology. Using artificial intelligence (AI), surgica...

Indication model for laparoscopic repeat liver resection in the era of artificial intelligence: machine learning prediction of surgical indication.

BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires a careful selection of indications. However, the ...