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Research Practical and Master Thesis topic for the University of Luxembourg. Natural language processing pipeline to extract HPO terms from clinical notes or EHR, annotate genes and diseases to the extracted terms and prioritize them by their frequency.

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Moshkante/myNLP2HPO_GenDis_pipeline

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Getting started

  • Go to the myNLP2HPO_GenDis_pipeline directory.

  • Replace test notes in the clinicalnotes folder with the desired clinical notes to analyze.

  • Run the meta shell script runanalysis.sh. The pipeline requires a stable internet connection!

  • Version 2 can be tested with the meta shell script runanalysis_v2.sh, which also requires internet connection. The folders created with the second version have the prefix "v2_". This version has an improved mapping process of the HPO term's synonyms to the clinical note.

  • Version 3 can be tested with the meta shell script runanalysis_v3.sh, which also requires internet connection. The folders created with the third version have the prefix "v3_". This version uses a more aggressive lemmatization method as well as an extended negation process.

Definition of folders created while running the shell script

  • /sources: contains three .tsv files, HPO_Terms.tsv with all HPO terms including synonyms and parent ids, HPO2Genes.tsv with genes linked to each HPO term and HPO2Diseases.tsv with diseases linked to each HPO term.
  • Following folders are related to the first version of the pipeline. Second and third version folders have gained the prefix "v2_" and "v3_", respectively.
  • /out_extracted_HPO: contains extracted HPO terms for each clinical note in the clinicalnotes folder as .txt files.
  • /out_annotated_genes: contains annotated genes for every extracted HPO term from the clinical notes as .txt files.
  • /out_prioritized_genes: contains genes prioritized and ranked by their frequency for each clinical note as .txt files.
  • /out_annotated_diseases: contains annotated diseases for every extracted HPO term from the clinical notes as .txt files.
  • /out_prioritized_diseases: contains diseases prioritized and ranked by their frequency for each clinical note as .txt files.

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Research Practical and Master Thesis topic for the University of Luxembourg. Natural language processing pipeline to extract HPO terms from clinical notes or EHR, annotate genes and diseases to the extracted terms and prioritize them by their frequency.

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