Back

Precision screening for cardiac amyloidosis using explainable AI: a threshold-optimised random forest pipeline with SHAP-based interpretability

28 August 2026 (15:15 - 16:00)
Organised by: Logo
Congress Presentation Part of: Artificial intelligence for cardiovascular phenotyping and precision risk prediction Machine Learning ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speakers

Photo
Mr Jonas Tuennermann

(Germany)

Photo
Doctor Moritz Brandt

University Medical Center of Mainz, Mainz (Germany)

7 More presentations in this session

Presentation thumbnail
Leveraging machine learning approaches to identify behavioural and lifestyle risk factors and predict mortality among people with cardiovascular disease
Ms R. Cong (AU)
Abstract Slides
Presentation thumbnail
Development and external validation of a novel echocardiography-based AI model for predicting aortic stenosis progression
Doctor K. Faierstein (Ramat Gan, IL)
Abstract Slides
Presentation thumbnail
Automated view selection tool delivers high accuracy across standard and handheld echocardiography: results from a government-funded project
Miss D. Pelin (Wurzburg, DE)
Abstract Slides
Presentation thumbnail
Interpretable dynamic graph learning for low-frequency cohorts: mapping pseudotime windows to CKM network dynamics
Doctor T. Liu (Tianjin, CN)
Abstract Slides
Presentation thumbnail
Proteomics-informed reconstruction of myocardial metabolism reveals profound bioenergetic failure in patients with anthracycline-induced cardiotoxicity
Doctor N. Beyhoff (Berlin, DE)
Abstract Slides

Access the full session

Session thumbnail
Artificial intelligence for cardiovascular phenotyping and precision risk prediction

The Event

Event poster

ESC Congress 2026

28 August 2026 15:15 CET
You may be interested in
thumbnail
Congress Presentation
Echocardiography machine learning based to improve detection of transthyretin cardiac amyloidosis: the R3M algorithm
22 May 2023
thumbnail
Congress Presentation
Machine-learned physiological signatures from the ECG predict sudden death in ischemic cardiomyopathy
4 April 2022
thumbnail
Congress Presentation
Identification of at-risk populations for cardiac amyloidosis: a multimodal machine learning development and validation study
31 August 2025
thumbnail
Congress Presentation
Multiple myeloma and al cardiac amyloidosis: the predictive role of HFA/ICOS risk score and other parameters
20 June 2025

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources