Deviation of Physiological from Chronological Age Is Associated with Health Lin PERETZ a and Nadav RAPPOPORT a,1 a Software and Information Systems Engineering, Ben-Gurion University of the Negev, ISRAEL Abstract. Biological age may be of higher importance than chronological age, yet biological age is not trivial to estimate. This study presents a regression model to predict age using routine clinical tests like laboratory tests using the UK Biobank (UKBB) data. We run different machine learning regression models for this predictions task and compare their performance according to RMSE. The models were trained using data from 472,189 subjects aged 37–82 years old and 61 different laboratory tests results. Our chosen model was an XGboost model, which achieved an RMSE of 6.67 years. Subjects whose the model predicted to be younger than their actual age were found to be healthier as they had fewer diagnoses, fewer operations, and had a lower prevalence of specific diseases than age-matched controls. On the other hand, subjects predicted to be older than their chronological age had no significant differences in the number of diagnoses, number of operations, and specific diseases than age-matched controls. Keywords. Biological age, Machine Learning, Laboratory tests, Chronological age, Electronic Health Records, BioBank 1. Introduction As the world's aging population grows at an unprecedented rate, there is a clear need to learn more about the biological aging process and the determinants of healthy aging. To achieve this goal, researchers seek biological markers and other factors that can track biophysiological aging and, ideally, provide insight into the underlying mechanisms [1,2,3,4]. Biological age (BA), also called physiological age, measures how well or poorly a person’s body functions. BA is correlated with calendar age (CA), also called chronological age, which is an objective measure of elapsed time since birth. The BA of a person can be higher or lower than their CA, since aging is not only a matter of time but is, in fact, a complex process with multiple causes. Studies have shown that young individuals of the same chronological age varied in their BA. These individuals showed cognitive decline and brain aging, self-reported worse health, and looked older [5]. There are several ways for determining BA, but none are definitive or truly accurate. Previous studies used a variety of ways to estimate the BA of a person. For example, studies used human physical activity as recorded by a wearable device [1], by cognitive variation independently of chronological age [6]. Other studies used molecular 1 Corresponding Author, Nadav Rappoport, Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, ISRAEL, 1 Ben-Gurion Boulevard, Beer-Sheva, ISRAEL; E-mail: nadavrap@bgu.ac.il. Challenges of Trustable AI and Added-Value on Health B. Séroussi et al. (Eds.) © 2022 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/SHTI220442 224