Predictive healthcare, driven by the availability of large medical datasets and computational advancements, plays a crucial role in enhancing patient care and optimizing healthcare system performance. However, training and deploying predictive models in healthcare presents substantial challenges, such as specialized expertise, and the need for state-of-the-art and costly hardware. To address these barriers, we introduce the Predictive Healthcare Platform (PHeP), an open-source platform designed to simplify the use of pre-trained models. Through a real-world case study, we showcase PHeP functionality in making advanced predictive healthcare accessible to users without extensive computational skills, or expensive computational resources. This will foster a wider adoption of predictive healthcare in medical practice.

PHeP: TrustAlert Open-Source Platform for Enhancing Predictive Healthcare with Deep Learning

Contaldo, Sandro Gepiro
Co-first
;
Pietropaolo, Emanuele
Co-first
;
Bosio, Lorenzo;Pernice, Simone;Terrone, Irene;Baccega, Daniele;Visconti, Alessia
;
Berchialla, Paola
Co-last
;
Beccuti, Marco
Co-last
2025-01-01

Abstract

Predictive healthcare, driven by the availability of large medical datasets and computational advancements, plays a crucial role in enhancing patient care and optimizing healthcare system performance. However, training and deploying predictive models in healthcare presents substantial challenges, such as specialized expertise, and the need for state-of-the-art and costly hardware. To address these barriers, we introduce the Predictive Healthcare Platform (PHeP), an open-source platform designed to simplify the use of pre-trained models. Through a real-world case study, we showcase PHeP functionality in making advanced predictive healthcare accessible to users without extensive computational skills, or expensive computational resources. This will foster a wider adoption of predictive healthcare in medical practice.
2025
19th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2024
Benevento, Italy
2024
Lecture Notes in Computer Science
Springer Science and Business Media Deutschland GmbH
15276 LNBI
206
216
9783031897030
9783031897047
deep learning; high performance computing; medical informatics; natural language processing; predictive healthcare
Contaldo, Sandro Gepiro; Pietropaolo, Emanuele; Bosio, Lorenzo; Pernice, Simone; Terrone, Irene; Baccega, Daniele; Wang, Yuting; Sahoo, Rahul Kumar; R...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2078474
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