The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Deep Learning Diabetes Monitoring and Prevention: Personalized Health Assistant Contribution
|
|
Author(s): Diogo Ribeiro (Polytechnic Institute of Guarda, Portugal), Celestino Gonçalves (Polytechnic Institute of Guarda, Portugal), Clara Silveira (Polytechnic Institute of Guarda, Portugal), Filipe Caetano (Polytechnic Institute of Guarda, Portugal)and Paulo Vieira (Polytechnic Institute of Guarda, Portugal)
Copyright: 2026
Pages: 40
Source title:
Reshaping Health Promotion and Disease Prevention Through Digital Innovation
Source Author(s)/Editor(s): Sónia Remondes Costa (University of Trás-os-Montes and Alto-Douro, Vila Real, Portugal)and Jorge Remondes (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal)
DOI: 10.4018/979-8-3373-3531-5.ch006
Purchase
|
Abstract
This chapter introduces the Personalized Health Assistant, an integrated system that combines Internet of Things devices, machine learning, and natural language processing to monitor diabetes and promote proactive, personalized healthcare. For diabetic patients, the system leverages wearable sensors data. For non-diabetic users, physiological parameters are inferred through lifestyle and stress indicators. To support predictive health monitoring, the system incorporates advanced machine learning models: Long Short-Term Memory, Multiple Back-Propagation, and a Convolutional Neural Network. Another component of the system is a clinically aware chatbot, built upon the Falcon-7B large language model and semantically validated using Bio_ClinicalBERT. The chatbot pipeline integrates FAISS-based context retrieval, clinical term detection, and semantic similarity scoring. The validation results underscore the system's reliability for predictive analytics, intelligent interaction, and real-time clinical support, making it a viable solution for scalable and secure chronic disease management.
Related Content
|
Muhammad Farooq Umer.
© 2026.
28 pages.
|
|
Awesh Khati, Anindita Das, Debajit Karmakar.
© 2026.
26 pages.
|
|
Minhaj Ahmed Qidwai, Mohammad Kabir Gawhari.
© 2026.
20 pages.
|
|
Fozia Asif, Minhaj Ahmed Qidwai.
© 2026.
14 pages.
|
|
Saurabh Chandra, Bhupinder Singh.
© 2026.
20 pages.
|
|
Anshika Tyagi, Vishal Jain.
© 2026.
26 pages.
|
|
Saleema Gulzar, Samina Subzali Vertejee, Tazeen Saeed Ali, Rozina Karmaliani.
© 2026.
16 pages.
|
|
|