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

Informacje na temat projektu

SMASH-HCM

Identyfikator umowy o grant: 101137115

DOI

10.3030/101137115

Data podpisania przez KE 8 Grudnia 2023

Data rozpoczęcia 1 Stycznia 2024

Data zakończenia 31 Grudnia 2027

Finansowanie w ramach

Health

Koszt całkowity

€ 8 546 366,25

Wkład UE

€ 8 546 366,25

8 546 366,25

Koordynowany przez

TAMPEREEN KORKEAKOULUSAATIO SR
Finland

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Rezultaty

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

Publikacje

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

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

Artificial intelligence applications in hypertrophic cardiomyopathy: turns and loopholes

Autorzy: 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
Opublikowane w: European Heart Journal - Digital Health, 2025, ISSN 2634-3916
Wydawca: Oxford University Press (OUP)
DOI: 10.1093/EHJDH/ZTAF086

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

Autorzy: Annariina Koivu, Mark Van Gils, Antti Ahola, Katriina Aalto-Setälä, Jari Hyttinen
Opublikowane w: Finnish Journal of eHealth and eWelfare, Numer 17, 2025, ISSN 1798-0798
Wydawca: Finnish Social and Health Informatics Association
DOI: 10.23996/FJHW.154831

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

Autorzy: Marion Taconné; Valentina D.A. Corino; Luca Mainardi
Opublikowane w: IEEE Open Journal of Engineering in Medicine and Biology, 2024, ISSN 2644-1276
Wydawca: 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

Autorzy: Kati Auranen, Dipak Kalra, Malte Von Tottleben, Shahan Tariq, Mark Van Gils
Opublikowane w: Finnish Journal of eHealth and eWelfare, Numer 17, 2025, ISSN 1798-0798
Wydawca: Finnish Journal of eHealth and eWelfare
DOI: 10.23996/FJHW.154635

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

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

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

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

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

Autorzy: Marion Taconne, Valentina Corino, Luca Mainardi
Opublikowane w: Computing in Cardiology Conference (CinC), 2024 Computing in Cardiology Conference (CinC), Numer 51, 2024, ISSN 2325-887X
Wydawca: Computing in Cardiology
DOI: 10.22489/CINC.2024.085

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

Autorzy: Francesca Menna, Joan Duprez, Marion Taconne, Adrien AL WAZZAN, Eleonore SERRANO, Lotfi Senhadji, erwan donal, Jari A. Hyttinen, Alfredo Hernandez, Virginie Le Rolle
Opublikowane w: Computing in Cardiology Conference (CinC), 2024 Computing in Cardiology Conference (CinC), Numer 51, 2024, ISSN 2325-887X
Wydawca: Computing in Cardiology
DOI: 10.22489/CINC.2024.240

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

Autorzy: Kati Auranen
Opublikowane w: 2024
Wydawca: Tampere University

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