Research Paper Volume 14, Issue 12 pp 4935—4958

Optimizing future well-being with artificial intelligence: self-organizing maps (SOMs) for the identification of islands of emotional stability

Fedor Galkin1, , Kirill Kochetov1, , Michelle Keller1, , Alex Zhavoronkov1,2,3, , Nancy Etcoff4, ,

  • 1 Deep Longevity Limited, Hong Kong
  • 2 Insilico Medicine, Hong Kong
  • 3 Buck Institute for Research on Aging, Novato, CA 94945, USA
  • 4 Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA

Received: February 5, 2022       Accepted: April 25, 2022       Published: June 20, 2022
How to Cite

Copyright: © 2022 Galkin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


In this article, we present a deep learning model of human psychology that can predict one’s current age and future well-being. We used the model to demonstrate that one’s baseline well-being is not the determining factor of future well-being, as posited by hedonic treadmill theory. Further, we have created a 2D map of human psychotypes and identified the regions that are most vulnerable to depression. This map may be used to provide personalized recommendations for maximizing one’s future well-being.


AI: Artificial intelligence; BMU: Best matching unit; CBT: Cognitive behavioral therapy; EN: Elastic net; MAE: Mean absolute error; MAPE: Mean absolute percentage error; MIDUS: Midlife in the United States study; MIDUS1: MIDUS wave 1995-1996; MIDUS2: MIDUS wave 2004-2006; SOM: Self-organizing map.