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| Hauptverfasser: | , , , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2504.03737 |
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| _version_ | 1866918103019945984 |
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| author | De Filippo, Giuseppe Singh, Simranjit Sisto, Gianpiero Mazzotta, Marco Mitrano, Gianvito Pascarelli, Claudio Fimiani, Gianluca Romano, Simone Lazoi, Mariangela Garofano, Marina Bramanti, Alessia |
| author_facet | De Filippo, Giuseppe Singh, Simranjit Sisto, Gianpiero Mazzotta, Marco Mitrano, Gianvito Pascarelli, Claudio Fimiani, Gianluca Romano, Simone Lazoi, Mariangela Garofano, Marina Bramanti, Alessia |
| contents | The management of chronic heart failure presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of exacerbations, and personalized treatment strategies. This paper presents the preliminary results of the PrediHealth research project conducted in this context. Specifically, it aims to address the challenges above by integrating telemedicine, mobile health solutions, and predictive analytics into a unified digital healthcare platform. We leveraged a web-based IoT platform, a telemonitoring kit with medical devices and environmental sensors, and AI-driven predictive models to support clinical decision-making. The project follows a structured methodology comprising research on emerging CPS/IoT technologies, system prototyping, predictive model development, and empirical validation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_03737 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PrediHealth: Telemedicine and Predictive Algorithms for the Care and Prevention of Patients with Chronic Heart Failure De Filippo, Giuseppe Singh, Simranjit Sisto, Gianpiero Mazzotta, Marco Mitrano, Gianvito Pascarelli, Claudio Fimiani, Gianluca Romano, Simone Lazoi, Mariangela Garofano, Marina Bramanti, Alessia Other Computer Science The management of chronic heart failure presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of exacerbations, and personalized treatment strategies. This paper presents the preliminary results of the PrediHealth research project conducted in this context. Specifically, it aims to address the challenges above by integrating telemedicine, mobile health solutions, and predictive analytics into a unified digital healthcare platform. We leveraged a web-based IoT platform, a telemonitoring kit with medical devices and environmental sensors, and AI-driven predictive models to support clinical decision-making. The project follows a structured methodology comprising research on emerging CPS/IoT technologies, system prototyping, predictive model development, and empirical validation. |
| title | PrediHealth: Telemedicine and Predictive Algorithms for the Care and Prevention of Patients with Chronic Heart Failure |
| topic | Other Computer Science |
| url | https://arxiv.org/abs/2504.03737 |