AIMC Topic: ROC Curve
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Establishment and validation of a risk stratification model for stroke risk within three years in patients with cerebral small vessel disease using a combined MRI and machine learning algorithm.
SLAS technology
Aug 21, 2024
BACKGROUND: Cerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a...
Ensemble learning-based pretreatment MRI radiomic model for distinguishing intracranial extraventricular ependymoma from glioblastoma multiforme.
NMR in biomedicine
Aug 20, 2024
This study aims to develop an ensemble learning (EL) method based on magnetic resonance (MR) radiomic features to preoperatively differentiate intracranial extraventricular ependymoma (IEE) from glioblastoma (GBM). This retrospective study enrolled p...
A machine learning-based prediction model for delayed clinically important postoperative nausea and vomiting in high-risk patients undergoing laparoscopic gastrointestinal surgery.
American journal of surgery
Aug 20, 2024
BACKGROUND: Delayed clinically important postoperative nausea and vomiting (CIPONV) could lead to significant consequences following surgery. We aimed to develop a prediction model for it using machine learning algorithms utilizing perioperative data...
Diagnosing Sarcopenia with AI-Aided Ultrasound (DINOSAUR)-A Pilot Study.
Nutrients
Aug 20, 2024
Sarcopenia has been recognized as a determining factor in surgical outcomes and is associated with an increased risk of postoperative complications and readmission. Diagnosis is currently based on clinical guidelines, which includes assessment of sk...
Machine Learning-Based Identification of Risk Factors of Keratoconus Progression Using Raw Corneal Tomography Data.
Cornea
Aug 20, 2024
PURPOSE: The purpose of this study was to identify early indicators of keratoconus progression in Pentacam data using machine learning (ML) techniques.
Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.
BMC medical imaging
Aug 20, 2024
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predict...
Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.
Journal of clinical monitoring and computing
Aug 19, 2024
PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive...
Humans
Artificial Intelligence
Algorithms
Databases, Factual
Middle Aged
Deep Learning
Monitoring, Intraoperative
ROC Curve
Photoplethysmography
Female
Reproducibility of Results
Aged
Adult
Male
Hypotension
Electrocardiography
Intraoperative Complications
Blood Pressure Determination
Consciousness Monitors
Blood Pressure
Blood Pressure Monitors
Area Under Curve
Capnography
Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.
Annals of medicine
Aug 19, 2024
BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm.
Development and internal validation of an artificial intelligence-assisted bowel sounds auscultation system to predict early enteral nutrition-associated diarrhoea in acute pancreatitis: a prospective observational study.
British journal of hospital medicine (London, England : 2005)
Aug 19, 2024
An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-...
Prediction of Arteriovenous Access Dysfunction by Mel Spectrogram-based Deep Learning Model.
International journal of medical sciences
Aug 19, 2024
The early detection of arteriovenous (AV) access dysfunction is crucial for maintaining the patency of vascular access. This study aimed to use deep learning to predict AV access malfunction necessitating further vascular management. This prospecti...
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