tanmaybasu/Qualitative-Text-Analysis-of-Healthcare-Data-Using-NLP
A text summarization framework to identify major opinions from healthcare text
This tool helps clinical researchers and healthcare practitioners quickly identify major themes and opinions from short-form text data, like patient feedback or survey responses. You provide a text file with individual responses (up to 160 characters each), and it outputs a CSV file summarizing the data into semantically similar clusters of terms, streamlining the qualitative analysis process. This is designed for anyone needing to efficiently make sense of large volumes of short textual input from healthcare participants.
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Use this if you are a clinical researcher or healthcare professional who needs to analyze open-ended survey responses, interview transcripts, or patient feedback and want to automate the process of identifying key themes and opinions.
Not ideal if your text data consists of very long documents, requires highly nuanced human interpretation for every segment, or is outside the domain of healthcare-related topics.
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Language
Python
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Last pushed
Mar 26, 2021
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