Evaluating the feasibility of the AI-powered Calcount smart diet smartphone application among healthcare workers in a pilot study

3 April 2025 (08:00 - 19:00)

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About the speaker

Ms Kotryna Elze Kuliesiute

Vilnius (Lithuania)

6 More presentations in this session

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Comparison of ECG-based neural networks for predicting atrial fibrillation across subgroups in the population

Mr B. Holderied (Greifswald, DE)

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A machine learning approach predicts response to physical exercise training using pulse wave analysis

Doctor B. Schmitz (Ennepetal, DE)

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Defining two dimensional transthoracic echocardiographic aorta dimension reference ranges in healthy subjects: a machine learning based model

Doctor A. Carbone (Naples, IT)

Abstract Slides

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Developing a personalized communication model using data-driven personas and clusters to enhance FH pediatric screening

Ms B. Cucos (Bucharest, RO)

Abstract Slides

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Development of the CARE-DM model to predict the risk of cardiovascular disease in older adults with type 2 diabetes

Ms V. Aponte Ribero (Bern, CH)

Abstract Slides

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Artificial intelligence and machine learning in risk prediction, prevention and care

The Event

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ESC Preventive Cardiology 2025

3 April - 5 April 2025

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ESC 365 is supported by

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ESC 365 is supported by

novartis

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