Enhancing the Human Health Status Prediction: the ATHLOS Project
Enhancing the Human Health Status Prediction: the ATHLOS Project
Abstract Preventive healthcare is a crucial pillar of health as it contributes to staying healthy and having immediate treatment when needed. Mining knowledge from longitudinal studies has the potential to significantly contribute to the improvement of preventive healthcare. Unfortunately, data originated from such studies are characterized by high complexity, huge volume and a plethora of missing values. Machine Learning, Data Mining and Data Imputation models are utilized as part of solving the aforementioned challenges, respectively. Towards this direction, we focus on the development of a complete methodology for the ATHLOS (Ageing Trajectories of Health: Longitudinal Opportunities and Synergies) Project - funded by the European Union’s Horizon 2020 Research and Innovation Program, which aims to achieve a better interpretation of the impact of aging on health. The inherent complexity of the provided dataset lie in the fact that the project includes 15 independent European and international longitudinal studies of aging. In this work, we particularly focus on the HealthStatus (HS) score, an index that estimates the human status of health, aiming to examine the effect of various data imputation models to the prediction power of classification and regression models. Our results are promising, indicating the critical importance of data imputation in enhancing preventive medicine’s crucial role.
Tasoulis Sotiris、Egea-Cort¨|s Laia、Scherbov Sergei、Tamosiunas Abdonas、Galas Aleksander、Haro Josep Maria、Anagnostou Panagiotis、Garc¨aa-Esquinas Esther、Bickenbach Jerome、Georgakopoulos Spiros、Plagianakos Vassilis、Vrahatis Aristidis G.、Ayuso-Mateos Jos¨| Luis、Prina Matthew、Panagiotakos Demosthenes、Bayes Ivet、Leonardi Matilde、Caballero Francisco F¨|lix、Sanchez-Niubo Albert
Department of Computer Science and Biomedical Informatics, University of ThessalyResearch, Innovation and Teaching Unit. Parc Sanitari Sant Joan de D¨|uInternational Institute for Applied Systems Analysis, World Population Program, Wittgenstein Centre for Demography and Global Human Capital||Austrian Academy of Science, Vienna Institute of Demography||Russian Presidential Academy of National Economy and Public Administration (RANEPA)Lithuanian University of Health SciencesDepartment of Epidemiology and Preventive Medicine, Jagiellonian UniversityResearch, Innovation and Teaching Unit. Parc Sanitari Sant Joan de D¨|u||Centro de Investigaci¨?n Biom¨|dica en Red de Salud MentalDepartment of Computer Science and Biomedical Informatics, University of ThessalyDepartment Preventive Medicine and Public Health, Universidad Aut¨?noma de Madrid/Idipaz||Centro de Investigaci¨?n Biom¨|dica en Red de Epidemiolog¨aa y Salud P¨2blicaSwiss Paraplegic Research, Guido A. Z?ch Institute (GZI)||Department of Health Sciences & Health Policy, University of LucerneDepartment of Computer Science and Biomedical Informatics, University of ThessalyDepartment of Computer Science and Biomedical Informatics, University of ThessalyDepartment of Computer Science and Biomedical Informatics, University of ThessalyCentro de Investigaci¨?n Biom¨|dica en Red de Salud Mental||Department of Psychiatry, Universidad Aut¨?noma de Madrid||Hospital Universitario de La Princesa, Instituto de Investigaci¨?n Sanitaria Princesa (IIS Princesa)Social Epidemiology Research Group. Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King?ˉs College London||Global Health Institute, King?ˉs College LondonDepartment of Nutrition and Dietetics, School of Health Science and Education, Harokopio UniversityResearch, Innovation and Teaching Unit. Parc Sanitari Sant Joan de D¨|u||Centro de Investigaci¨?n Biom¨|dica en Red de Salud MentalFondazione IRCCS Istituto Neurologico Carlo Besta, MilanDepartment Preventive Medicine and Public Health, Universidad Aut¨?noma de Madrid/Idipaz||Centro de Investigaci¨?n Biom¨|dica en Red de Epidemiolog¨aa y Salud P¨2blicaResearch, Innovation and Teaching Unit. Parc Sanitari Sant Joan de D¨|u||Centro de Investigaci¨?n Biom¨|dica en Red de Salud Mental
预防医学医学研究方法生物科学研究方法、生物科学研究技术
ImputationVtreatBig dataHealthcarePrediction
Tasoulis Sotiris,Egea-Cort¨|s Laia,Scherbov Sergei,Tamosiunas Abdonas,Galas Aleksander,Haro Josep Maria,Anagnostou Panagiotis,Garc¨aa-Esquinas Esther,Bickenbach Jerome,Georgakopoulos Spiros,Plagianakos Vassilis,Vrahatis Aristidis G.,Ayuso-Mateos Jos¨| Luis,Prina Matthew,Panagiotakos Demosthenes,Bayes Ivet,Leonardi Matilde,Caballero Francisco F¨|lix,Sanchez-Niubo Albert.Enhancing the Human Health Status Prediction: the ATHLOS Project[EB/OL].(2025-03-28)[2025-08-18].https://www.medrxiv.org/content/10.1101/2021.01.19.21250076.点此复制
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