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Jonas Richiardi

Publications and source records attributed to Jonas Richiardi.

2 recordsLinked to original sources
PubMed2025

Study Protocol for HeartMagic: A Prospective Observational Cohort Characterizing Subtypes of Heart Failure With Preserved Ejection Fraction.

BACKGROUND: Heart failure (HF) is a life-threatening syndrome with significant morbidity and mortality. Although evidence-based drug treatments have effectively reduced morbidity and mortality in HF with reduced ejection fraction (EF), few therapies have been demonstrated to improve outcomes in HF with preserved EF. This may be caused by the existence of several HF with preserved EF subtypes that each need different treatments. There is therefore an unmet need for a comprehensive approach to subtype patients with HF with preserved EF. This protocol details the approach employed in the HeartMagic (Heart Failure Studied With a Machine Learning, Genomics, and Imaging Combination) study to address this gap. METHODS: This prospective multicenter observational cohort study will include 500 consecutive patients with HF with preserved EF at 2 Swiss university hospitals, along with 50 age-matched patients with HF with reduced EF and 50 healthy controls. In addition to routine clinical workup, participants undergo genomic, transcriptomic, and metabolomic analyses, and the anatomy, composition, and function of the heart are quantified by comprehensive echocardiography and magnetic resonance imaging. Quantitative magnetic resonance imaging is also applied to characterize the kidney. The primary outcome is a composite of 1-year cardiovascular mortality or rehospitalization. Machine learning-based multimodal clustering will be employed to identify distinct HF with preserved EF subtypes. Statistical analysis will include group comparisons, survival analysis, and integrative multimodal clustering combining clinical, imaging, ECG, genomic, transcriptomic, and metabolomic data to identify and validate HF with preserved EF subtypes. CONCLUSIONS: The integration of comprehensive magnetic resonance imaging with extensive genomic and metabolomic profiling in this study will result in an unprecedented panoramic view of HF with preserved EF and help distinguish functional subgroups, which may provide a basis for personalized therapies.

Aged↗
PubMed2006

Multimodal biometrics for identity documents (MBioID).

The MBioID initiative has been set up to address the following germane question: What and how biometric technologies could be deployed in identity documents in the foreseeable future? This research effort proposes to look at current and future practices and systems of establishing and using biometric identity documents (IDs) and evaluate their effectiveness in large-scale developments. The first objective of the MBioID project is to present a review document establishing the current state-of-the-art related to the use of multimodal biometrics in an IDs application. This research report gives the main definitions, properties and the framework of use related to biometrics, an overview of the main standards developed in the biometric industry and standardisation organisations to ensure interoperability, as well as some of the legal framework and the issues associated to biometrics such as privacy and personal data protection. The state-of-the-art in terms of technological development is also summarised for a range of single biometric modalities (2D and 3D face, fingerprint, iris, on-line signature and speech), chosen according to ICAO recommendations and availabilities, and for various multimodal approaches. This paper gives a summary of the main elements of that report. The second objective of the MBioID project is to propose relevant acquisition and evaluation protocols for a large-scale deployment of biometric IDs. Combined with the protocols, a multimodal database will be acquired in a realistic way, in order to be as close as possible to a real biometric IDs deployment. In this paper, the issues and solutions related to the acquisition setup are briefly presented.

Biometry↗