Howard Moskowitz¹*, Stephen Rappaport², Sharon Wingert³, Angelica DiLorenzo⁴, Sunaina Saharan⁵ and Taylor Mulvey⁶

¹Cognitive Behavioral Insights, Inc., Albany, NY, USA
²SDR Consulting, Norwalk, CT, USA
³Tactical Data Group, Stafford, VA, USA
⁴Medical University of Lublin, Lublin, Poland
⁵Government Medical College, Patiala, India
⁶St. Thomas More School, Oakdale, CT, USA

*Corresponding Author: Howard Moskowitz, Cognitive Behavioral Insights, Inc., Albany, NY, USA.

Received: March 13, 2024; Published: March 24, 2024

Abstract

This paper presents a novel approach to understanding how to learn about food preferences of people who cannot communicate due to advanced FTD (Fronto-temporal dementia). The approach combines Mind Genomics discoveries of mind-sets in the world of everyday experience with the power of AI, artificial intelligence (Socrates as a Service). The paper shows how to present AI with the appropriate queries in the Mind Genomics platform (bimileap.com). The queries suggests to AI the existence of basic mind-sets for food preference, but do not specify the nature of such mind-sets. The queries allow the user to learn about different types of such preference mind-sets, as well as how to observe the behavior of FTD sufferers, and deduce their preference. The approach is presented as a new way to learn the practicalities of caring for patients, a way that can be customized to the user and to the issued being confronted and requiring a practical solution.

Keywords: Hallmark; FTD (Fronto-Temporal Dementia); Artificial Intelligence

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Citation

Citation: Howard Moskowitz., et al. “Deducing Food Preferences for Fronto-dementia Sufferers: What Might be Discovered Using Mind Genomics Thinking Incorporated into Artificial Intelligence".Acta Scientific Nutritional Health 8.4 (2024): 57-64.

Copyright

Copyright: © 2024 Howard Moskowitz., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.