Memantic: A Medical Knowledge Discovery Engine by Alexei Yavlinsky.
Abstract:
We present a system that constructs and maintains an up-to-date co-occurrence network of medical concepts based on continuously mining the latest biomedical literature. Users can explore this network visually via a concise online interface to quickly discover important and novel relationships between medical entities. This enables users to rapidly gain contextual understanding of their medical topics of interest, and we believe this constitutes a significant user experience improvement over contemporary search engines operating in the biomedical literature domain.
Alexei takes advantage of prior work on medical literature to index and display searches of medical literature in an “economical” way that can enable researchers to discover new relationships in the literature without being overwhelmed by bibliographic detail.
You will need to check my summary against the article but here is how I would describe Memantic:
Memantic indexes medical literature and records the co-occurrences of terms in every text. Those terms are mapped into a standard medical ontology (which reduces screen clutter). When a search is performed, the “results are displayed as nodes based on the medical ontology and includes relationships established by the co-occurrences found during indexing. This enables users to find relationships without the necessity of searching through multiple articles or deduping their search results manually.
As I understand it, Memantic is as much an effort at efficient visualization as it is an improvement in search technique.
Very much worth a slow read over the weekend!
I first saw this in a tweet by Sami Ghazali.
PS: I tried viewing the videos listed in the paper but wasn’t able to get any sound? Maybe you will have better luck.