Two former students of the Data Analytics and Visualization program have produced an app that allows users to get an instant diagnosis and treatment of an injury.
Maridor Bocalbos and Dean Pienica, both class of 2019, developed the app, called Image2Txt.Doc, as master’s students in their Data Product Design course at the Katz School of Science and Health. With the app, patients can speak with a chatbot that asks for information about their injury. They are then given the option to either speak with a clinician or continue chatting. If they continue chatting, they will be asked to send a picture of their injury which is then given an immediate diagnosis and treatment. If patients want to speak with a clinician, the app searches for a clinician in their area based on their insurance information.
For the chatbot to work, Bocalbos and Pienica use the Intent Recognition Natural Language Processing Engine, an artificial intelligence that deals with machine-reading comprehension which determines the proper responses and options that patients can choose from based on their answers to questions asked by the chatbot. To recognize the image, the Convolutional Neural Network, most commonly applied to analyzing visual imagery, is used to predict the type of injury.
Bocalbos cited the time and effort in scheduling a doctor’s appointment, long waiting times during an emergency or urgent care visit, and the increasing cost of healthcare as the factors inspiring their efforts. She said that during the testing phase of the app, nine out of 10 users said they’d buy it for their own personal use.
“The app would be especially useful during the pandemic since most patients are scared to go to the hospital for fear of getting COVID-19,” she said.
Bocalbos and Pienica were given the Investment Award after the app was judged by experts in both artificial intelligence and product design for presentation, user value, business value, prototype, analytics, and insights.
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