Stratification, Management, and Guidance of Hypertrophic Cardiomyopathy Patients using Hybrid Digital Twin Solutions

Informations projet

SMASH-HCM

N° de convention de subvention: 101137115

DOI

10.3030/101137115

Date de signature de la CE 8 Decembre 2023

Date de début 1 Janvier 2024

Date de fin 31 Decembre 2027

Financé au titre de

• Health

Coût total

€ 8 546 366,25

Contribution de l’UE

€ 8 546 366,25

Coordonné par

TAMPEREEN KORKEAKOULUSAATIO SR
Finland

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (15)

Quality assurance plan

Documents standards, processes and ways of working

Risk assessment reports

Risk and quality assessment

Requirements for disease patients' self-management

Requirements spec. for patient view of disease self-management

SMASH-HCM solution as research tool requirements

Technical and non-technical specification for the tool in a continued research setting

Dissemination, communication and exploitation plan

Strategy documents

Ethical approval of the whole SMASH-HCM study

Approval distributed to centers collecting clinical data

Initial Data-driven models

Data-driven models and biomarkers available

Design specifications of an API for DSS algorithms

API’s functionality is specified

Initial Evidence-based models and biomarkers

Evidence-based models and biomarkers available

VASC Submission package

Ethical approval and EU clinical trials registration

Libraries of HCM populations of cellular electromechanical models
Requirements SMASH-HCM solution in clinical practice – initial

Technical and non-technical requirements for the SMASH-HCM solution

PILOT Submission package

Approvals by all clinical partners

Governance report

Specifies decision-making processes and project-related bodies’ members

Requirements SMASH-HCM predictive/clustering tool

Requirement specifications for predictive/clustering tool for HCM patient stratification

Websites, patent fillings, videos etc. (1)

Project Website

Published project website.

Other (1)

Contact with regulatory agencies FIMEA, DEKRA

Discussions with FIMEA and DEKRA representatives performed

Data Management Plan (1)

Project Data Management Plan (P-DMP)

Documents management of project (non-research) data.

Publications

Peer reviewed articles (6)

Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing

Auteurs: Julia Camps, Zhinuo Jenny Wang, Ruben Doste, Lucas Arantes Berg, Maxx Holmes, Brodie Lawson, Jakub Tomek, Kevin Burrage, Alfonso Bueno-Orovio, Blanca Rodriguez
Publié dans: Medical Image Analysis, Numéro 100, 2024, ISSN 1361-8415
Éditeur: Elsevier BV
DOI: 10.1016/J.MEDIA.2024.103361

Artificial intelligence applications in hypertrophic cardiomyopathy: turns and loopholes

Auteurs: Giorgia Panichella, Manuel Garofalo, Laura Sasso, Alessandra Milazzo, Alessandra Fornaro, Josè Manuel Pioner, Alfonso Bueno-Orovio, Mark van Gils, Annariina Koivu, Luca Mainardi, Virginie Le Rolle, Felix Agakov, Maurizio Pieroni, Katriina Aalto-Setälä, Jari Hyttinen, Iacopo Olivotto, Annamaria Del Franco
Publié dans: European Heart Journal - Digital Health, 2025, ISSN 2634-3916
Éditeur: Oxford University Press (OUP)
DOI: 10.1093/EHJDH/ZTAF086

Digitaalisen kaksosteknologian hyödyntäminen terveydenhuollossa: Hyödyt ja vaikutukset hypertrofisen kardiomyopatian tapaustutkimuksen valossa

Auteurs: Annariina Koivu, Mark Van Gils, Antti Ahola, Katriina Aalto-Setälä, Jari Hyttinen
Publié dans: Finnish Journal of eHealth and eWelfare, Numéro 17, 2025, ISSN 1798-0798
Éditeur: Finnish Journal of eHealth and eWelfare
DOI: 10.23996/FJHW.154831

An ECG-Based Model for Left Ventricular Hypertrophy Detection: A Machine Learning Approach

Auteurs: Marion Taconné; Valentina D.A. Corino; Luca Mainardi
Publié dans: IEEE Open Journal of Engineering in Medicine and Biology, 2024, ISSN 2644-1276
Éditeur: IEEE
DOI: 10.1109/OJEMB.2024.3509379

Defining functional requirements for a self-management solution for Hypertrophic Cardiomyopathy patients – a multi-stakeholder multi-framework approach

Auteurs: Kati Auranen, Dipak Kalra, Malte Von Tottleben, Shahan Tariq, Mark Van Gils
Publié dans: Finnish Journal of eHealth and eWelfare, Numéro 17, 2025, ISSN 1798-0798
Éditeur: Finnish Journal of eHealth and eWelfare
DOI: 10.23996/FJHW.154635

Multilevel modelling for decision support in hypertrophic cardiomyopathy in the SMASH-HCM project

Auteurs: Alpo Olavi Värri; Mark Van Gils; Jari Hyttinen
Publié dans: Finnish Journal of eHealth and eWelfare, 2024, ISSN 1798-0798
Éditeur: Finnish Social and Health Informatics Association
DOI: 10.23996/FJHW.143516

Book chapters (1)

Evaluating Convolution, Attention, and Mamba Based U-Net Models for Multi-class Bi-Atrial Segmentation from LGE-MRI

Auteurs: Claas Thesing, Alfonso Bueno-Orovio, Abhirup Banerjee
Publié dans: Lecture Notes in Computer Science, Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers., 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-87756-8_22

Conference proceedings (2)

Automatic Right Ventricular Hypertrophic Detection Integrating Electrocardiography-based QRS Biomarkers with Machine Learning

Auteurs: Marion Taconne, Valentina Corino, Luca Mainardi
Publié dans: Computing in Cardiology Conference (CinC), 2024 Computing in Cardiology Conference (CinC), Numéro 51, 2024
Éditeur: Computing in Cardiology
DOI: 10.22489/CINC.2024.085

Model-based Analysis of Myocardial Strains in Obstructive and Non-obstructive Hypertrophic Cardiomyopathy

Auteurs: Francesca Menna, Joan Duprez, Marion Taconne, Adrien AL WAZZAN, Eleonore SERRANO, Lotfi Senhadji, erwan donal, Jari A. Hyttinen, Alfredo Hernandez, Virginie Le Rolle
Publié dans: Computing in Cardiology Conference (CinC), 2024 Computing in Cardiology Conference (CinC), Numéro 51, 2024
Éditeur: Computing in Cardiology
DOI: 10.22489/CINC.2024.240

Thesis and dissertations (1)

Integrated Requirements Engineering for Digital Health: Enhancing Self-Care in Hypertrophic Cardiomyopathy Management

Auteurs: Kati Auranen
Publié dans: 2024
Éditeur: Tampere University