AIMC Topic: Predictive Value of Tests

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Classification Method of ECG Signals Based on RANet.

Cardiovascular engineering and technology
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias.

Machine learning approach for prediction of outcomes in anticoagulated patients with atrial fibrillation.

International journal of cardiology
BACKGROUND: The accuracy of available prediction tools for clinical outcomes in patients with atrial fibrillation (AF) remains modest. Machine Learning (ML) has been used to predict outcomes in the AF population, but not in a population entirely on a...

An explainable machine learning model to predict early and late acute kidney injury after major hepatectomy.

HPB : the official journal of the International Hepato Pancreato Biliary Association
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 ...

Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Acute kidney injury (AKI) is not only a complication but also a serious threat to patients with cerebral infarction (CI). This study aimed to explore the application of interpretable machine learning algorithms in predicting AKI in patien...

A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.

Journal of thrombosis and haemostasis : JTH
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 ...

Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study.

European journal of pediatrics
Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In thi...

A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software.

The international journal of cardiovascular imaging
Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the mos...