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InfoSys 2025 Congress
March 09, 2025 to March 13, 2025 - Lisbon, Portugal
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March 09, 2025 to March 13, 2025 - Lisbon, Portugal
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April 06, 2025 to April 10, 2025 - Valencia, Spain
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April 06, 2025 to April 10, 2025 - Valencia, Spain
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May 18, 2025 to May 22, 2025 - Nice, France
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May 18, 2025 to May 22, 2025 - Nice, France
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IARIA Congress 2025, The 2025 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications
July 06, 2025 to July 10, 2025 - Athens, Greece
DigiTech 2025 Congress
July 06, 2025 to July 10, 2025 - Athens, Greece
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NexTech 2025 Congress
September 28, 2025 to October 02, 2025 - Lisbon, Portugal
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September 28, 2025 to October 02, 2025 - Lisbon, Portugal
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SocSys 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain
NetWare 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain
- SENSORCOMM 2025, The Nineteenth International Conference on Sensor Technologies and Applications
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- FASSI 2025, The Eleventh International Conference on Fundamentals and Advances in Software Systems Integration
- GREEN 2025, The Tenth International Conference on Green Communications, Computing and Technologies
- HEALTHINFO 2025, The Tenth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing
TechWorld 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain
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ThinkMind // GLOBAL HEALTH 2023, The Twelfth International Conference on Global Health Challenges // View article global_health_2023_1_70_70097
Towards Personalized Wellness: Detection and Analysis of Homogeneous Communities in Multi-Modal Biomedical Networks
 Authors:
Rama Krishna Thelagathoti
Hesham H. Ali Keywords: Homogeneous groups; Network Analysis; Mobility Analysis; Personalized interventions. Abstract:
In recent years, personalized wellness has attracted significant attention by many research groups. However, distinguishing between various groups associated with different health conditions, which is critical to achieve personalized healthcare, remains a complex challenge. The driving force behind this study is to harness the potential of biomedical networks to reveal homogenous groups with a high degree of similarity. Our primary goal is to uncover hidden relationships that may not be evident using traditional data analysis by discerning interaction patterns and similarities between nodes in the network. To construct a biomedical graph, we integrated mobility data and medical data, mainly Heart Rate Variability (HRV) data, for each subject, representing them as nodes. The edges between nodes reflect the similarity between subjects in both mobility patterns and HRV responses. Leveraging advanced network analysis techniques, we applied an appropriate network features to identify strongly connected homogenous groups within the graph. These groups represent subsets of subjects displaying highly similar mobility characteristics and HRV patterns. Our analysis identified five highly similar groups within the biomedical network based on the subjects mobility and HRV data. Remarkably, mobility features played a more pronounced role in the formation of these groups compared to HRV data, suggesting strong ties and similarities in mobility characteristics. These findings significantly contribute to our understanding of the interplay between movement behaviors, offering promising avenues for personalized interventions and enhanced clinical decision-making in the pursuit of advanced healthcare and improved well-being. Pages: 38 to 43 Copyright: Copyright (c) IARIA, 2023 Publication date: September 25, 2023 Published in: conference ISSN: 2308-4553 ISBN: 978-1-68558-112-1 Location: Porto, Portugal Dates: from September 25, 2023 to September 29, 2023
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