Surgery

A calculator for musculoskeletal injuries prediction in surgeons: a machine learning approach.

BACKGROUND: Surgical specialists experience significant musculoskeletal strain as a consequence of their profession, a domain within the healthcare system often recognized for the pronounced impact of such issues. The aim of this study is to calculate the risk of presenting musculoskeletal injuries in surgeons after surgical practice.

Variability of morphology in photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment.

We investigated fluctuations of the photoplethysmography (PPG) waveform in patients undergoing surgery. There is an association between the morphologic variation extracted from arterial blood pressure (ABP) signals and short-term surgical outcomes. The underlying physiology could be the numerous regulatory mechanisms on the cardiovascular system. We hypothesized that similar information might exis...

Salivary detection of Chikungunya virus infection using a portable and sustainable biophotonic platform coupled with artificial intelligence algorithms.

The current detection method for Chikungunya Virus (CHIKV) involves an invasive and costly molecular biology procedure as the gold standard diagnostic...

Perforator Selection with Computed Tomography Angiography for Unilateral Breast Reconstruction: A Clinical Multicentre Analysis.

: Despite CTAs being critical for preoperative planning in autologous breast reconstruction, experienced plastic surgeons may have differing preferenc...

Integrating StEP-COMPAC definition and enhanced recovery after surgery status in a machine-learning-based model for postoperative pulmonary complications in laparoscopic hepatectomy.

BACKGROUND: Postoperative pulmonary complications (PPCs) contribute to high mortality rates and impose significant financial burdens. In this study, a...

German sugar beet farmers' intention to use autonomous field robots for seeding and weeding.

Robotic weed control is not yet widely adopted, despite its technological availability and proven economics and sustainability in crop cultivation by ...

Advanced Non-linear Modeling and Explainable Artificial Intelligence Techniques for Predicting 30-Day Complications in Bariatric Surgery: A Single-Center Study.

PURPOSE: Metabolic bariatric surgery (MBS) became integral to managing severe obesity. Understanding surgical risks associated with MBS is crucial. Di...

Main challenges on the curation of large scale datasets for pancreas segmentation using deep learning in multi-phase CT scans: Focus on cardinality, manual refinement, and annotation quality.

Accurate segmentation of the pancreas in computed tomography (CT) holds paramount importance in diagnostics, surgical planning, and interventions. Rec...

MRI-compatible and sensorless haptic feedback for cable-driven medical robotics to perform teleoperated needle-based interventions.

PURPOSE: Surgical robotics have demonstrated their significance in assisting physicians during minimally invasive surgery. Especially, the integration...

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its main risk factor is reportedly intraoperative proc...

Machine Learning-Based Prediction of Chronic Shunt-Dependent Hydrocephalus After Spontaneous Subarachnoid Hemorrhage.

BACKGROUND: Chronic posthemorrhagic hydrocephalus often arises following spontaneous subarachnoid hemorrhage (SAH). Timely identification of patients ...

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals.

This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialy...

Artificial intelligence in interventional radiology: Current concepts and future trends.

While artificial intelligence (AI) is already well established in diagnostic radiology, it is beginning to make its mark in interventional radiology. ...

Development of Machine Learning Models for Predicting the 1-Year Risk of Reoperation After Lower Limb Oncological Resection and Endoprosthetic Reconstruction Based on Data From the PARITY Trial.

BACKGROUND: Oncological resection and reconstruction involving the lower extremities commonly lead to reoperations that impact patient outcomes and he...

Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets.

The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the pati...

Magnetic Torque-Driven All-Terrain Microrobots.

All-terrain microrobots possess significant potential in modern medical applications due to their superior maneuverability in complex terrains and con...

Effect of machine learning models on clinician prediction of postoperative complications: the Perioperative ORACLE randomised clinical trial.

BACKGROUND: Anaesthesiologists might be able to mitigate risk if they know which patients are at greatest risk for postoperative complications. This t...

Clinical Application of Artificial Intelligence in Prediction of Intraoperative Cerebrospinal Fluid Leakage in Pituitary Surgery: A Systematic Review and Meta-Analysis.

BACKGROUND: Postoperative cerebrospinal fluid (CSF) leakage is the leading adverse event in transsphenoidal surgery. Intraoperative CSF (ioCSF) leakag...

"Identifying complication risk factors in reduction mammaplasty: a single-center analysis of 1021 patients applying machine learning methods".

Various surgical approaches and pedicles have been described to ensure safe and satisfactory results in reduction mammaplasty. Although different brea...

Intermediate-grained kernel elements pruning with structured sparsity.

Neural network pruning provides a promising prospect for the deployment of neural networks on embedded or mobile devices with limited resources. Altho...