AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Postoperative Complications

Showing 161 to 170 of 924 articles

Clear Filters

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life. This study aimed to evaluate the performance of five machine learning (ML) algorithms for predicti...

Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

Journal of neurosurgery
OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently devel...

Predicting early return to the operating room in early-onset scoliosis patients using machine learning techniques.

Spine deformity
PURPOSE: Surgical treatment of early-onset scoliosis (EOS) is associated with high rates of complications, often requiring unplanned return to the operating room (UPROR). The aim of this study was to create and validate a machine learning model to pr...

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

Scientific reports
We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learning algorithms. The artificial intelligence prediction models were built in Python, primarily using ar...

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy.

Journal of endourology
Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectomy. Although nomograms exist, their retrospective limitations highlight artificial intelligence (AI)'...

Long-term outcomes of robot-assisted versus minimally invasive esophagectomy in patients with thoracic esophageal cancer: a propensity score-matched study.

World journal of surgical oncology
BACKGROUND: Recently, robot-assisted minimally invasive esophagectomy (RAMIE) has gained popularity worldwide. Some studies have compared the long-term results of RAMIE and minimally invasive esophagectomy (MIE). However, there are no reports on the ...

A Pilot Study Using Machine-learning Algorithms and Wearable Technology for the Early Detection of Postoperative Complications After Cardiothoracic Surgery.

Annals of surgery
OBJECTIVE: To evaluate whether a machine-learning algorithm (ie, the "NightSignal" algorithm) can be used for the detection of postoperative complications before symptom onset after cardiothoracic surgery.

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to p...

Development and validation of 'Patient Optimizer' (POP) algorithms for predicting surgical risk with machine learning.

BMC medical informatics and decision making
BACKGROUND: Pre-operative risk assessment can help clinicians prepare patients for surgery, reducing the risk of perioperative complications, length of hospital stay, readmission and mortality. Further, it can facilitate collaborative decision-making...