MOLECULAR SCIENCES AND APPLICATIONS
Print ISSN: 2944-9138, E-ISSN: 2732-9992 An Open Access International Journal of Molecular Sciences and Applications
Volume 4, 2024
Artificial Intelligence and Machine Learning with Moment Generating Functions to Enhance Biological Count Data Analysis
Authors: , ,
Abstract: This research presents artificial intelligence with supervised machine learning to determine the median count
given training data from biological laboratory experimentation. After determining the central moment of the median,
machine learning is then used to predict the population median value. When computer programs learn they access available
data, then autonomously analyze the information to make informed, data-driven decisions. Moment generating function
restrictions identify a parameter of interest by restricting the expected value of the moment generating function. This
research proposes a theoretical foundation for achieving such predictions. A summary of the key elements underlying the
statistical power of the Mann– Whitney test, a nonparametric hypothesis test for the median of count data, is also presented.
A nonparametric approach allows for accurate predictions while relaxing distributional assumptions such as normality.
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Keywords: Artificial Intelligence, Machine Learning, Moment Generating Function, Nonparametric Statistics, Mann-
Whitney and Statistical Power
Pages: 42-45
DOI: 10.37394/232023.2024.4.5