We are hugely delighted to continue our successful partnership with HopHacks – the bi-annual hackathon hosted at Johns Hopkins University in Baltimore, Maryland.
For 36 hours students work in teams of up to four people, to bring a software or hardware idea to life. Last spring, they gathered more than 300 of the most creative and talented students from JHU, MIT, UMD, CMU, Rutgers, NYU, and many more. This fall, even more students from institutions across the country showed up on September 15-17. It was a very special and inspiring weekend as engineers, designers, and entrepreneurs were all brought together to explore new ideas, compete for prizes, and create amazing applications. Teams started working no stop on their hacks from 9:00 PM on Friday evening and continued until Sunday morning 9:00 AM.
Bowen Li, the creator of Request2D, has been awarded as John Snow Labs’ Best Use of Healthcare Dataset
Request2D aims to help medical researchers to find data files related with their research questions in their own dataset or database.
For every research project with secondary use of clinical data, researchers doubt about the availability of data in their database, and the location of data columns which are related to the research question to query. For a clinician without data science knowledge, this could be a tough process, traditionally they need help from informationists. ReQuest2D will help them to finish this process all by themselves.
Why ReQuest2D is limited to medicine field? Making use of existing medical ontologies and standards, such as ICD 10, SNOMED, is the key. For example, if we care about glaucoma, the system will search ICD 10 and SNOMED ontology, to find all concepts related to glaucoma, and then go to the database, find all columns that include concepts of our research interest.
What it does
Automatically search related medical concepts for researchers. Map the concepts to datasets. Come with part of data quality service.
Django does not support ajax query to do file reading, which was a time killer.
This project really solves the most annoying problem that we’re facing with every day.
Try it out