Surgery

Machine learning for temporary stoma after intestinal resection in surgical decision-making of Crohn's disease.

BACKGROUND: Crohn's disease (CD) often necessitates surgical intervention, with temporary stoma creation after intestinal resection (IR) being a crucial decision. This study aimed to construct novel models based on machine learning (ML) to predict temporary stoma formation after IR for CD.

Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). We employed only the clinical phases derived from video analysis as input to the algorithms. Our results show that InceptionTime and LSTM-FCN yielded the most accurate predictions. InceptionTime achieves Mean Absolute Error (MA...

Constitutive neural networks for main pulmonary arteries: discovering the undiscovered.

Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological condi...

SERPINA3: A Novel Therapeutic Target for Diabetes-Related Cognitive Impairment Identified Through Integrated Machine Learning and Molecular Docking Analysis.

Diabetes-related cognitive impairment (DCI) is a severe complication of type 2 diabetes mellitus (T2DM), with limited understanding of its molecular m...

Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery.

PURPOSE: Several surgical-skill assessment tools emphasize the importance of efficient tissue-dissection, whose assessment relies on human judgment an...

Machine learning-based prediction of post-induction hypotension: identifying risk factors and enhancing anesthesia management.

BACKGROUND: Post-induction hypotension (PIH) increases surgical complications including myocardial injury, acute kidney injury, delirium, stroke, prol...

Towards Rapid and Low-Cost Stroke Detection Using SERS and Machine Learning.

Stroke affects approximately 12 million individuals annually, necessitating swift diagnosis to avert fatal outcomes. Current hospital imaging protocol...

Towards precision medicine strategies using plasma proteomic profiling for suspected gallbladder cancer: A pilot study.

BACKGROUND & AIMS: Currently, preoperative diagnostic methods that can distinguish cancer from benign disease of the gallbladder are insufficient, and...

Early prediction of 30-day mortality in patients with surgical wound infections following cardiothoracic surgery: Development and validation of the SWICS-30 score utilizing conventional logistic regression and artificial neural network.

INTRODUCTION: We aimed to create and validate the 30-day prognostic score for mortality in patients with surgical wound infection (SWICS-30) after car...

Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.

BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myocardial injury (PMI), and thereby increased postoper...

Artificial intelligence-based model to predict recurrence after local excision in T1 rectal cancer.

BACKGROUND: According to current guideline, patients with resected specimens showing high-risk features are recommended additional surgery after local...

Machine Learning-Driven Modeling to Predict Postdischarge Venous Thromboembolism After Pancreatectomy for Pancreas Cancer.

BACKGROUND: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While nati...

Soft Pressure Sensor Array Inspired by Human Skin for Detecting 3D Robotic Movement.

3D soft pressure sensors play an important role in precise robotic operations. Multimodal soft pressure sensors that detect both static and dynamic pr...

Machine learning or traditional statistical methods for predictive modelling in perioperative medicine: A narrative review.

Prediction of outcomes in perioperative medicine is key to decision-making and various prediction models have been created to help quantify and commun...

Comparison of surgical approaches to the hippocampal formation with artificial intelligence.

The relatively complex functional anatomy of the mediobasal temporal region makes surgical approaches to this area challenging. Several studies descri...

Head-mounted surgical robots are an enabling technology for subretinal injections.

Therapeutic protocols involving subretinal injection, which hold the promise of saving or restoring sight, are challenging for surgeons because they a...

Optimal design of a wheelchair-mounted robotic arm for activities of daily living.

PURPOSE: The increasing prevalence of upper limb dysfunctions due to stroke, spinal cord injuries, and multiple sclerosis presents a critical challeng...

Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology.

OBJECTIVE: With the development of day surgery, the characteristics of "short, frequent and fast" ophthalmic surgery are becoming more prominent. Howe...

Cooperative Magnetic Interfacial Microrobot Couple for Versatile Non-Contact Biomedical Applications.

Magnetic interfacial microrobots are increasingly recognized as a promising approach for potential biomedical applications ranging from electronic fun...

Applying deep learning and the ecological home range concept to document the spatial distribution of Atlantic salmon parr (Salmo salar L.) in experimental tanks.

Measuring and monitoring fish welfare in aquaculture research relies on the use of outcome- (biotic) and input-based (e.g., abiotic) welfare indicator...