Acta Scientific Nutritional Health (ASNH)(ISSN: 2582-1423)

Review Article Volume 8 Issue 4

Deducing Food Preferences for Fronto-dementia Sufferers: What Might be Discovered Using Mind Genomics Thinking Incorporated into Artificial Intelligence

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


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 ( 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: 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: © 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.


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