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Study using NLP and ML techniques to analyze 461,789 PubMed abstracts related to aging published between 1925 and 2023

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aging_literature

An unsupervised analysis of aging research literature using NLP and ML techniques to analyze 461,789 PubMed abstracts related to aging published between 1925 and 2023. Data_preprocessing contains the code needed to preprocess the native text from PubMed. Each notebook corresponds to the code needed to generate each figure in the manuscript. lda_visualization is an html file that allows interactive visualization of the LDA model.

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Study using NLP and ML techniques to analyze 461,789 PubMed abstracts related to aging published between 1925 and 2023

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