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Summarization Web Application

Poster for our project on Web application for summary generation of interviews for research studies.

Client Matt Stoll
Professor(s) Mejdi Eraslan Melissa Sienkiewicz
Program Computer Programming
Students Gurminder Singh Badwal, Segikwiye Ilan, Peiwen Ilan, Yuvraj Singh Na, Mingzi Xu

Project Description:

This project is a high-impact initiative designed to revolutionize the client’s process for managing and analyzing interview transcriptions and summaries. Currently, students manually transcribe interviews with clinicians and rely on ChatGPT for individual summaries. However, this approach is both time-consuming and lacks a centralized, scalable storage solution for efficient data management.

The new application will automate the entire summarization workflow, leveraging GPT technology in the background. Users will be able to upload interview transcripts, auto-generate summaries, and categorize them by subject area (e.g., cardiology, neurology). Additionally, the application will feature cross-summary functionality, allowing for comprehensive analyses within each category.

This system represents a strategic shift from small-scale, manual processing to automated platform capable of handling large volumes of data. By streamlining these processes, the project will enable stakeholders to access and analyze interview insights more effectively, significantly enhancing both scalability and usability.


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