AIMC Topic: Predictive Value of Tests
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Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.
JACC. Cardiovascular interventions
Oct 30, 2024
BACKGROUND: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully automated) provides real-time, objective, and reproducible quantitative analysis of coronary angiography without requiring additional time or labor.
Time Factors
Treatment Outcome
Predictive Value of Tests
Tomography, Optical Coherence
Female
Automation
Aged
Coronary Vessels
Male
Middle Aged
Humans
Coronary Angiography
Coronary Artery Disease
Artificial Intelligence
Percutaneous Coronary Intervention
Stents
Prospective Studies
Image Interpretation, Computer-Assisted
Republic of Korea
Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement.
Cardiovascular and interventional radiology
Oct 29, 2024
PURPOSE: To determine the association of machine learning-derived CT body composition and 90-day mortality after transjugular intrahepatic portosystemic shunt (TIPS) and to assess its predictive performance as a complement to Model for End-Stage Live...
Early prediction of radiotherapy outcomes in pharyngeal cancer using deep learning on baseline [18F]Fluorodeoxyglucose positron emission Tomography/Computed tomography.
European journal of radiology
Oct 29, 2024
OBJECTIVES: This study aimed to develop an integrated segmentation-free deep learning (DL) framework to predict multiple aspects of radiotherapy outcome in pharyngeal cancer patients by analyzing pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron...
Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions.
The Korean journal of internal medicine
Oct 29, 2024
Acute kidney injury (AKI) is a significant health challenge associated with adverse patient outcomes and substantial economic burdens. Many authors have sought to prevent and predict AKI. Here, we comprehensively review recent advances in the use of ...
Predicting Portal Pressure Gradient in Patients with Decompensated Cirrhosis: A Non-invasive Deep Learning Model.
Digestive diseases and sciences
Oct 28, 2024
BACKGROUND: A high portal pressure gradient (PPG) is associated with an increased risk of failure to control esophagogastric variceal hemorrhage and refractory ascites in patients with decompensated cirrhosis. However, direct measurement of PPG is in...
Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.
Abdominal radiology (New York)
Oct 26, 2024
PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular carcinoma (HCC) for the prediction of response to Yttrium 90 radiation segmentectomy.
Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.
Obesity surgery
Oct 25, 2024
PURPOSE: Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited for patients with severe obesity and nonalcoholic fatty liver disease (NAFLD). We developed machine learning (ML) models to predict significant liver...
Using Atrial Fibrillation Burden Trends and Machine Learning to Predict Near-Term Risk of Cardiovascular Hospitalization.
Circulation. Arrhythmia and electrophysiology
Oct 24, 2024
BACKGROUND: Atrial fibrillation is associated with an increased risk of cardiovascular hospitalization (CVH), which may be triggered by changes in daily burden. Machine learning of dynamic trends in atrial fibrillation burden, as measured by insertab...
Intraoperative Hypotension Prediction: Current Methods, Controversies, and Research Outlook.
Anesthesia and analgesia
Oct 23, 2024
Intraoperative hypotension prediction has been increasingly emphasized due to its potential clinical value in reducing organ injury and the broad availability of large-scale patient datasets and powerful machine learning tools. Hypotension prediction...
Machine learning-based prediction of sarcopenia in community-dwelling middle-aged and older adults: findings from the CHARLS.
Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
Oct 23, 2024
BACKGROUND: Sarcopenia is a prominent issue among aging populations and associated with poor health outcomes. This study aimed to examine the predictive value of questionnaire and biomarker data for sarcopenia, and to further develop a user-friendly ...
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