The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach
Authors:
- Giacinto Angelo SgarroGSGiacinto Angelo Sgarro
- Luca GrilliLuca Grilli
- Anna Antonia ValenzanoAVAnna Antonia Valenzano
- Fiorenzo MoscatelliFiorenzo Moscatelli
- Domenico MonacisDMDomenico Monacis
- Giusi TotoGTGiusi Toto
- Antonella De MariaAMAntonella De Maria
- Giovanni MessinaGMGiovanni Messina
- Rita PolitoRita Polito
Open Access
- 6 July 2023
- journal article
- research article
- Published by MDPI AG in Diagnostics
- Vol. 13 (13) , 2292
Abstract
Osteoporosis is a common musculoskeletal disorder among the elderly and a chronic condition which, like many other chronic conditions, requires long-term clinical management. It is caused by many factors, including lifestyle and obesity. Bioelectrical impedance analysis (BIA) is a method to estimate body composition based on a weak electric current flow through the body. The measured voltage is used to calculate body bioelectrical impedance, divided into resistance and reactance, which can be used to estimate body parameters such as total body water (TBW), fat-free mass (FFM), fat mass (FM), and muscle mass (MM). This study aims to find the tendency of osteoporosis in obese subjects, presenting a method based on hierarchical clustering, which, using BIA parameters, can group patients who show homogeneous characteristics. Grouping similar patients into clusters can be helpful in the field of medicine to identify disorders, pathologies, or more generally, characteristics of significant importance. Another added value of the clustering process is the possibility to define cluster prototypes, i.e., imaginary patients who represent models of “states”, which can be used together with clustering results to identify subjects with similar characteristics in a classification context. The results show that hierarchical clustering is a method that can be used to provide the detection of states and, consequently, supply a more personalized medicine approach. In addition, this method allowed us to elect BIA as a potential prognostic and diagnostic instrument in osteoporosis risk development.Keywords
Funding Information
- Project MiSE-DGPIIPMI—Artificial Intelligence to support the digitalization and industrial engineering process—2021
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