What's going on with the App Challenge now?Quick answer: a lot!
IBM staff member Frank Greco and Cornelia Bailey are to apply IBM’s BlueMix Technology (including Watson) and other tools to a variety of teaching data sources. Read more...
App Challenge developers will be exploring the limits of Optical Character Recognition to read numbers from a racetrack tote board and build a mobile minimum viable product. Read more...
IT Services staff Rose Pezzuti-Dyer is developing a simple proof-of-concept for a voice-enabled version of EngAGE for the Amazon Echo. Read more...
IT Services staff Fritz Anderson and Cornelia Bailey built an iOS app based on Dan's clinical needs for pre-operative patient evaluation. Dan will test the efficacy of his app in an IRB-approved study later in 2017.
Dr. Rubin presented the Step Test app during the May Grand Rounds of the Department of Anesthesiology.
IT Services staff Bill Brown and Tommy Thomas built an Android counterpart of the current Triple iOS app, doubling the audience for the Triple team. While this includes typical Android programming practices, we've also had to understand and use Unity, the standard for game creation.
Alex and Chris presented the Triple work at a May meeting of Asychronous Anonymous, an initiative to foster learning and collaborative opportunities in tech at UChicago. For more information, visit https://www.triple.io/
IT Services staff Alex Clark and Cornelia Bailey are took the EngAGE web MVP from the 2016 app challenge, and preparedit for a second round of participatory testing with elderly users later in 2017. This included updating the site according to best practices for elders, discussing the possibilities of an Alexa integration, and making sure a minimum of 2-way communication is possible from the site.
Dr. Huisingh-Scheetz presented the work at the April 2017 Geriatrics and Palliative Medicine Grand Round and at the 2017 Innovation Fest Kickoff.
IBM staff member Frank Greco and Cornelia Bailey are continued to apply IBM’s BlueMix Technology (including Watson) and other tools to Ballot Ready's manual workflow of gathering high-quality content for voter education. In the 2016 Cognitive Computing Challenge, we figured out how to systematically help with categorizing candidate stances (e.g. Education, Environment, etc). In this round of work, we applied the same and new machine learning tools to figure out if a given webpage contains meaningful candidate stances or endorsements.
The Ballot Ready team presented on this work in February 2017 as part of the Polsky Center's UChicago Technology Summit.