Challenges
Understanding How Medical Conditions are Related
Medical conditions are related to each other like a family tree. There are broad conditions that include more specific ones, and so on. We call these relationships "parent" and "child."
It's easy to see that "lung cancer" is a child of "cancer." But, for more specific conditions, it gets tricky. For example, "oat cell carcinoma" and "small cell lung cancer" what’s the parent, and what’s the child? (Trick question - they're siblings!)
After a lot of thought, we came up with a method that solved this problem nicely and gave us a complete map of how conditions are related. This method is fully automated, and doesn’t require any human effort to construct this mapping! Plus, we figured out how to solve this problem ahead of time for many conditions, so we didn't have to do as much math for every search.
Making it Fast
This system needed to give fast results while looking at a huge number of clinical trials and medical terms. We had to rank over 65,000 clinical trials for each search, while also checking against millions of medical terms to make sure our results were accurate. And we needed to do all this in just a few seconds, even for searches the system had never seen before!
To make this possible, we:
1. Used statistics to pre-calculate key condition families and match those to common searches.
2. Made different levels of search, so we could give the most obvious results right away while doing a deeper search in the background.
3. Finetuned our AI model to work best for our specific needs.
End Result
ClinicalNet now has a search engine that matches patients with highly relevant clinical trials across over a million unique conditions in 5 seconds or less.
Our new search system gives much more relevant results than the old one, without taking much more time in most cases.
Plus, our method for building the condition relationships saved over 1000 hours of manual work, and it automatically includes any new conditions.
By creating custom AI models and using smart engineering solutions, we were able to solve this tough problem in a clever way!