Choosing a Primary Care Physician — How AI Powered by Mind Genomics Thinking Provides Direction

Howard R Moskowitz^1,2*, Sunaina Saharan³, Stephen D Rappaport⁴ and Sharon Wingert^1
1Tactical Data Group, Stafford, Virginia, USA
²Mind Genomics Associates, Inc., White Plains, New York, USA
³Government Medical College and Hospital, Patiala, Punjab, India
⁴Stephen D. Rappaport Consulting LLC, Norwalk, Connecticut, USA
*Corresponding Author: Howard R. Moskowitz, Tactical Data Group, Stafford, VA, USA and Mind Genomics Associates, Inc., White Plains, NY, USA.

Published: January 06, 2025

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Abstract  

This research examines the characteristics individuals utilize when selecting a primary care provider in their local area. The paper demonstrates the utility of employing large language models (LLM) like ChatGPT 5 to: define a scenario, prompt the model to respond with various perspectives, key aspects relevant to those perspectives, exhibit thought processes of the perspectives, and then conduct an in-depth analysis of the model's generated information. The complete analysis enables the user to get a thorough understanding of a subject within 30 minutes cost-effectively, quickly, and with the option to make revisions. The method is shown in this paper and may be used in other scenarios where human attitudes are crucial. The approach does not presuppose the accuracy of clinical or technical aspects, which may be readily confirmed by other scientific disciplines. The goal is to improve early-stage thinking by exploring how individuals perceive a situation.

Keywords: Generative AI; Large Language Models in Healthcare Research; Mind Genomics; Primary Care Physician Selection

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