AI Cancer Review Writer

Created by team biologyAI on January 21, 2024

Review articles in scientific journals are a helpful way for researchers to learn the state of the art in a field from leading names in the field. In the field of cancer treatment, there are many such review articles in the literature. One common issue with review articles is that they are almost immediately out of date, that is, as soon as a new article is published with new data that changes the scientific consensus about a problem, the review article will not have this information. In addition, many review articles are published in prestigious journals, which means that they are often expensive and thereby inaccessible to a large part of the world. We have sketched out an AI in this hackathon that writes up to date literature reviews from the very latest literature, downloaded fresh from Entrez PubMed, a vast archive of biological abstracts, with millions of peer-reviewed abstracts about cancer. We use this information along with Retrieval Augmented Generation to generate sentences for a new article, where each sentence is based on one from a chosen literature review article.

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"I would love to test the app someday, however the proposed solution need a lot of improvement specially on the technical side. Keep up the good work! "


Muhammad Inaamullah

Machine Learning Engineer

"Currently, the built solution is not complete. No demo is available. The GitHub repository contains multiple files that use a single GPT-4 prompt message. The presentation lacks a demo of the app as well. It is potentially a good business value, but the app needs to be complete."


Nikita Ladyzhnikov

Lead Frontend Engineer @ Clarifai