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review · Applied and Computational Mathematics

Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review

20241 citationOpen accessUniversity of Nairobi

Abstract

The application of Hidden Markov Models (HMMs) in the study of genetic and neurological disorders has shown significant potential in advancing our understanding and treatment of these conditions. This review assesses 77 papers selected from a pool of 1,105 records to evaluate the use of HMMs in disease research. After the exclusion of duplicate and irrelevant records, the papers were analyzed for their focus on HMM applications and regional representation. A notable deficiency was identified in research across regions such as Africa, South America, and Oceania, emphasizing the need for more diverse and inclusive studies in these areas. Additionally, many studies did not adequately address the role of genetic mutations in the onset and progression of these diseases, revealing a critical research gap that warrants further investigation. Future research efforts should prioritize the examination of mutations to deepen our understanding of how these changes impact the development and progression of genetic and neurological disorders. By addressing these gaps, the scientific community can facilitate the development of more effective and personalized treatments, ultimately enhancing health outcomes on a global scale. Overall, this review highlights the importance of HMMs in this area of research and underscores the necessity of broadening the scope of future studies to include a wider variety of geographical regions and a more comprehensive investigation of genetic mutations.

Research topics

  • Genomics and Rare Diseases
  • Genetic Associations and Epidemiology
  • Genomic variations and chromosomal abnormalities

Sustainable Development Goals

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DOI: 10.11648/j.acm.20241304.11

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