Caffeine vs. Guarana: Can AI Predict Which Stimulant Packs the Bigger Punch?
Faculty Mentor
Ahmed Abu Fayyad
Major/Area of Research
Pharmacy, Herbal, AI
Description
INTRODUCTION: This systematic literature review explores the potential of artificial intelligence (AI) in predicting the stimulant effects of caffeine compared to Gera, a lesser-known stimulant. Caffeine, a widely consumed psychoactive substance, is known for its ability to enhance alertness and improve cognitive performance. In contrast, Gera, derived from the plant species *Catha edulis*, has gained attention for its stimulant properties but remains under-researched in comparison to affeine.
METHOD: The review synthesizes existing studies that examine the pharmacological mechanisms, subjective effects, and physiological responses associated with both stimulants. By leveraging AI algorithms, this research aims to analyze large datasets from clinical studies, user-reported outcomes, and biochemical analyses to discern patterns and predict the relative stimulant effects of caffeine and Gera.
CONCLUSION: The findings will contribute to a deeper understanding of how these substances influence human cognition and behavior and highlight the potential of AI as a tool for research in psychopharmacology. This systematic review not only aims to clarify the stimulant effects of caffeine and Gera but also seeks to demonstrate the efficacy of AI in synthesizing and interpreting complex data, paving the way for future studies in the field. Through this exploration, we aim to establish a framework for utilizing AI in predicting the effects of various stimulants, which could have significant implications for health, wellness, and the food and beverage industry.
Caffeine vs. Guarana: Can AI Predict Which Stimulant Packs the Bigger Punch?
INTRODUCTION: This systematic literature review explores the potential of artificial intelligence (AI) in predicting the stimulant effects of caffeine compared to Gera, a lesser-known stimulant. Caffeine, a widely consumed psychoactive substance, is known for its ability to enhance alertness and improve cognitive performance. In contrast, Gera, derived from the plant species *Catha edulis*, has gained attention for its stimulant properties but remains under-researched in comparison to affeine.
METHOD: The review synthesizes existing studies that examine the pharmacological mechanisms, subjective effects, and physiological responses associated with both stimulants. By leveraging AI algorithms, this research aims to analyze large datasets from clinical studies, user-reported outcomes, and biochemical analyses to discern patterns and predict the relative stimulant effects of caffeine and Gera.
CONCLUSION: The findings will contribute to a deeper understanding of how these substances influence human cognition and behavior and highlight the potential of AI as a tool for research in psychopharmacology. This systematic review not only aims to clarify the stimulant effects of caffeine and Gera but also seeks to demonstrate the efficacy of AI in synthesizing and interpreting complex data, paving the way for future studies in the field. Through this exploration, we aim to establish a framework for utilizing AI in predicting the effects of various stimulants, which could have significant implications for health, wellness, and the food and beverage industry.