Deep Suggest

Query Expansion and Refinement

DeepSuggest is a query expansion and refinement tool. Considering more than 70% of healthcare information is stored in unstructured clinical notes, healthcare providers increasingly demand effective text-search systems for clinical care, QI reporting and research projects. However, clinical notes are known for containing spelling variations, typos, local-practice-generated acronyms, synonyms, and informal words. We developed a novel search system (DeepSuggest) that can guide users to expand their input query by suggesting spelling variations, acronyms and other semantically relevant words, all identified through an artificial intelligence (AI)-driven unsupervised shallow learning algorithm, designed by our our Natural Language Processing team. Users can filter by note type or the date notes were written. In addition to number of notes, encounters, and patients that match the search criteria, we also provide users with the distribution of note types, and an estimated number of notes with the keyword of interest being used in a context of negation, risk of, or patient history. De-identify mode allows users to use this system for demo purposes or taking screenshots, and export option enables them to export the results for further analysis. DeepSuggest was tested and validated at Nationwide Children’s Hospital with over 50 million clinical notes.

Sample screenshots for suggestions:

Deep Suggest

Watch the Demo

Watch the Testimonial

Academic & Commercial License

Implementation of DeepSuggest in another institute requires approximately 80 hours of IT work with provided step-by-step documentation from NCH. We are offering 30 hours of free technical support to first 2 non-commercial organization interested to try DeepSuggest.


R&D division at the Research Institute at Nationwide Children’s Hospital, Columbus, OH