Epistemic AI platform accelerates innovation by connecting biomedical knowledge

TL;DR

The paper introduces an Epistemic AI platform that leverages knowledge graphs, NLP, and network analysis to accelerate biomedical discovery by uncovering hidden connections and simplifying research workflows.

Contribution

It presents a novel web-based platform combining knowledge mapping, NLP, and machine learning to enhance biomedical research and discovery.

Findings

Enables construction of detailed biological knowledge maps

Reduces research time by organizing complex data

Identifies hidden biomedical connections effectively

Abstract

Epistemic AI accelerates biomedical discovery by finding hidden connections in the network of biomedical knowledge. The Epistemic AI web-based software platform embodies the concept of knowledge mapping, an interactive process that relies on a knowledge graph in combination with natural language processing (NLP), information retrieval, relevance feedback, and network analysis. Knowledge mapping reduces information overload, prevents costly mistakes, and minimizes missed opportunities in the research process. The platform combines state-of-the-art methods for information extraction with machine learning, artificial intelligence and network analysis. Starting from a single biological entity, such as a gene or disease, users may: a) construct a map of connections to that entity, b) map an entire domain of interest, and c) gain insight into large biological networks of knowledge. Knowledge maps provide clarity and organization, simplifying the day-to-day research processes.