A Retrospective Review of Biomedical Applications of Neutrosophic Probability Distributions

This paper provides a comprehensive review of the applications of Neutrosophic probability distributions in biomedical research. Rooted in the philosophy of Neutrosophy, these distributions explicitly model uncertainty through truth, indeterminacy, and falsity components, offering a flexible and nuanced framework for analyzing complex and imprecise biomedical data. Compared to traditional statistical methods, Neutrosophic approaches demonstrate superior performance in handling interval-valued, vague, and indeterminate information commonly encountered in biomedical studies. We discuss their advantages, such as enhanced modeling of uncertainty and robustness to assumption violations, alongside limitations including interpretability challenges and the need for standardized tools. Future research directions are outlined to foster the development of novel distributions, software implementations, and validation techniques. This review underscores the significant potential of Neutrosophic probability distributions to advance biomedical data analysis, particularly in emerging fields such as personalized medicine and genomics.