Surgery

Quantifying the biomimicry gap in biohybrid robot-fish pairs.

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulations to reality, using robotics to validate the modeling hypotheses. This challenge arises in bridging what we term the 'biomimicry gap', which is...

Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.

This study aimed to develop and validate a machine learning (ML) model tailored to the Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for predicting the development of cardiovascular disease (CVD), a major chronic complication in these patients. We used data from two cohorts, namely the discovery (one hospital; n = 12,809) and validation (two hospitals; n = 201...

Sensory Attenuation With a Virtual Robotic Arm Controlled Using Facial Movements.

When humans generate stimuli voluntarily, they perceive the stimuli more weakly than those produced by others, which is called sensory attenuation (SA...

Data-driven prediction of continuous renal replacement therapy survival.

Continuous renal replacement therapy (CRRT) is a form of dialysis prescribed to severely ill patients who cannot tolerate regular hemodialysis. Howeve...

Real-Time Tool Localization for Laparoscopic Surgery Using Convolutional Neural Network.

Partially automated robotic systems, such as camera holders, represent a pivotal step towards enhancing efficiency and precision in surgical procedure...

Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can res...

A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage.

RATIONALE AND OBJECTIVES: Early identification for hematoma expansion can help improve patient outcomes. Presently, there are many methods to predict ...

An artificial intelligence-designed predictive calculator of conversion from minimally invasive to open colectomy in colon cancer.

Minimally invasive surgery is safe and effective in colorectal cancer. Conversion to open surgery may be associated with adverse effects on treatment ...

Development and validation of a machine learning predictive model for perioperative myocardial injury in cardiac surgery with cardiopulmonary bypass.

BACKGROUND: Perioperative myocardial injury (PMI) with different cut-off values has showed to be associated with different prognostic effect after car...

ChatGPT-4 Performs Clinical Information Retrieval Tasks Using Consistently More Trustworthy Resources Than Does Google Search for Queries Concerning the Latarjet Procedure.

PURPOSE: To assess the ability of ChatGPT-4, an automated Chatbot powered by artificial intelligence, to answer common patient questions concerning th...

Harnessing artificial intelligence for predicting and managing postoperative pain: a narrative literature review.

PURPOSE OF REVIEW: This review examines recent research on artificial intelligence focusing on machine learning (ML) models for predicting postoperati...

A novel virtual robotic platform for controlling six degrees of freedom assistive devices with body-machine interfaces.

Body-machine interfaces (BoMIs)-systems that control assistive devices (e.g., a robotic manipulator) with a person's movements-offer a robust and non-...

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessm...

A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study.

BACKGROUND: Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication fo...

Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks.

BACKGROUND CONTEXT: Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disorder in elderly people and usually first seen by pr...

Reducing annotating load: Active learning with synthetic images in surgical instrument segmentation.

Accurate instrument segmentation in the endoscopic vision of minimally invasive surgery is challenging due to complex instruments and environments. De...

Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.

BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of concentrated red blood cells due to preoperative anem...

Diagnosis to dissection: AI's role in early detection and surgical intervention for gastric cancer.

Gastric cancer remains a formidable health challenge worldwide; early detection and effective surgical intervention are critical for improving patient...

Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit.

This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of in-hospital mortality risk in patients with sponta...

Development of a machine learning-based risk model for postoperative complications of lung cancer surgery.

PURPOSE: To develop a comorbidity risk score specifically for lung resection surgeries.