Journal of cardiovascular computed tomography
Apr 24, 2024
INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™...
BACKGROUND: The application of deep learning methods in rapid bone scintigraphy is increasingly promising for minimizing the duration of SPECT examinations. Recent works showed several deep learning models based on simulated data for the synthesis of...
HPB : the official journal of the International Hepato Pancreato Biliary Association
Apr 23, 2024
BACKGROUND: Risk assessment models for acute kidney injury (AKI) after major hepatectomy that differentiate between early and late AKI are lacking. This retrospective study aimed to create a model predicting AKI through machine learning and identify ...
BMC medical informatics and decision making
Apr 23, 2024
BACKGROUND: This study aims to propose a semi-automatic method for monitoring the waiting times of follow-up examinations within the National Health System (NHS) in Italy, which is currently not possible to due the absence of the necessary structured...
Journal of thrombosis and haemostasis : JTH
Apr 19, 2024
BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for ...
Journal of the American Heart Association
Apr 19, 2024
BACKGROUND: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predi...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 16, 2024
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...
AIMS: Machine learning models can use image and text data to predict the number of years since diabetes diagnosis; such model can be applied to new patients to predict, approximately, how long the new patient may have lived with diabetes unknowingly....
PURPOSE: Posterior circulation ischemic stroke (PCIS) possesses unique features. However, previous studies have primarily or exclusively relied on anterior circulation stroke cases to build machine learning (ML) models for predicting onset time. To d...
BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative...
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