# Finding Hidden Relationships Between Medical Concepts by Leveraging Metamap and Text Mining Techniques

arXiv: https://arxiv.org/abs/2606.07540 · HTML: https://mlsanity.com/paper/2606.07540/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 20 references that are in the map.
- First posted on arXiv 30 Apr 2026.

## Builds on (most cited first, 1 of 1)

- [Refinement of Pipe-and-Filter Architectures](https://mlsanity.com/paper/1411.2414/) (2014)

## Abstract (arXiv)

Text is one of the most common ways to store data in this computerized world. At a glance, it may seem that those data are not interconnected. But in reality, data can have hidden connections. Therefore, in this research, a new model has been presented that can find hidden relationships between two medical concepts by using MetaMap and appropriate text-mining techniques. Specifically, the model creates a new comprehensive index structure and can find cross-document hidden links connecting topics of interest that most existing approaches have ignored. Experiments show the effectiveness of the proposed model in discovering new connections between topics.