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This is an implementation of text mining and topic modelling to analyze research trend in the context of leprosy from year 1966 to 2024.

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Riyaaa1/Leprosy-trend-analysis

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Context

Leprosy (also called Hansen's disease) is a chronic infectious disease caused by the bacteria Mycobacterium leprae. It is one of the twenty Neglected Tropical Diseases(NTDs), identified by WHO. Neglected Tropical Diseases (NTDs), including leprosy, are called "neglected" primarily because they mostly affect populations in tropical and subtropical regions, particularly in low- and middle-income countries and are almost absent from the global health agenda. This leads to limited knowledge, resources, fundings, a cycle of poor educational outcomes and professional opportunities; in addition, are associated with stigma and social exclusion. Formerly endemic, Nepal declared the elimination of leprosy as a public health concern at the national level in early 2010. Nevertheless, the disease persists in the southern regions of the country, specifically affecting 17 districts in the Terai region.

Objective

  • Examine the research topics explored in leprosy studies over the years
  • Identify prevailing patterns (if any), such as dominant research topics observed in specific time period
  • Identify Single nucleotide polymorphisms (SNPs) associated with susceptibility and severity patterns among leprosy patients

Table of Contents

1. Data Source

All the research articles used in this study was retrieved from NCBI's PubMed database using Biopython's entrez module. NCBI PubMed is home to one of the biggest collection of biomedical and life science journals. Other NCBI databases such as GEO, GenBank and many more can also be accessed using entrez utilities.

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This is an implementation of text mining and topic modelling to analyze research trend in the context of leprosy from year 1966 to 2024.

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