caramel2001 / archmed

ArchMed

Reading research papers has never been easier..

URL to the Application : http://10.91.113.144:8501

Inspiration

The goal of this project is to improve the accessibility and comprehension of scientific research papers for people working in the biomedical sector. Research publications are frequently written in technical language that is challenging for non-experts to understand, making it more difficult for them to stay current on the most recent research and use it in their work. This project intends to bridge the gap between technical research and practical application by simplifying complex articles and breaking them down into simple concepts. This will enable people in the biomedical industry to stay informed and use the most recent research to better their work.

What it does

The project provides a selection of tools made to increase the usability and accessibility of research articles. The initiative makes it possible for users to immediately understand the main ideas of a given document by distilling lengthy research papers into concise summaries and presenting them in slide style. Additionally, the project makes use of keyword analysis to give readers a deeper grasp of the subjects and ideas that were covered in the article. Users can also engage in a chat feature that provides answers to questions related to the research papers. Finally, the project offers paper recommendations based on the user's interests and reading history. All of these features work together to make research papers more digestible and increase their practical applications in the real world.

How we built it

We have utilised pre-trained State-Of-The-Art Transformer Architecture models - BioLinkBERT (Base) and T5 for Question-Answering and Text Summarisation tasks. These models were determined after a very rigorous and thorough analysis as shown on next slide..

Accomplishments that we're proud of

Our end-to-end deployed system gives the user to interact and understand the document in a way never done before!

1. KEYWORD ANALYSIS : Understanding the distribution of words across the document.
2. TEXT SUMMARIZATION : Generating concise summaries of sections in the document
3. SLIDE DECK GENERATION : Reproducing the contents of the document in the form of a simple, short and aesthetic PPT
4. RECOMMENDATION SYSTEM : Providing suggestions to users based on relevance and upcoming latest trends.

What we learned

Deployment using Streamlit package. Google Slides API documentation. HuggingFace transformer inference as well as pre-trained checkpoints.

What's next for ArchMed

1. Citation Networks for recommender system.
2. Using Generative AI to produce explanatory videos.
3. Containerisation (Docker/Kubernetes) to improve scalability.

About us

We are a diverse and equally qualified group of penultimate-year students from Nanyang Technological University, Singapore.