AIMC Topic: Predictive Value of Tests

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Deep Learning for Cardiac Overload Estimation - Predicting B-Type Natriuretic Peptide (BNP) Levels From Heart Sounds and Electrocardiogram.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: B-type natriuretic peptide (BNP) and N-terminal pro-BNP (NT-pro-BNP) are key biomarkers used for heart failure (HF) management. Although traditional auscultation lacks objective evaluation, the SSS01-series phonocardiogram enables rapid r...

Moving beyond the syndrome: how can acute kidney injury phenotypes help?

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: The purpose of this review is to describe recent and important updates in acute kidney injury (AKI) phenotyping that help us to move beyond the clinical syndrome of AKI.

Predicting takotsubo syndrome subtypes: An interpretable machine learning model for differentiating emotional versus physical aetiologies.

International journal of cardiology
BACKGROUND: Takotsubo syndrome (TTS) is an acute coronary syndrome characterized by a reversible, mostly apical dysfunction of the left ventricle. Based on the triggering event, TTS has been classified as primary due to emotional causes and secondary...

A plasma metabolome-derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank.

Diabetes, obesity & metabolism
AIMS: Severe liver disease (SLD) in nonalcoholic fatty liver disease (NAFLD) is often diagnosed late due to the long asymptomatic period of progressive fibrosis. We aimed to identify metabolomic profiles associated with SLD and develop a predictive m...

Identification of neurological text markers associated with risk of stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...

Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

Techniques in coloproctology
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...

The performance of machine learning models in predicting postpartum depression: a meta-analysis and systematic review.

Journal of reproductive and infant psychology
AIM: To evaluate the effectiveness of machine learning (ML) approaches in predicting individuals with postpartum depression (PPD), this study systematically reviewed and meta-analysed existing evidence.

Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.

Italian journal of pediatrics
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...