Feb - May, 2020
Syashi, Isabel, Maddy- Industry based project. Feedback from IBM Watson designers
CAREO
Careo is a health app that harnesses machine learning capabilities to enable a patient with chronic conditions to translate, prioritize, and analyze their data into a useful and understandable format — prior to a doctor’s visit?
"Well laid out research and amazing job at utilizing NLP and LLM capabilities for helping patients with chronic health conditions"
- IBM Watson designers
My Role
As the project was collaborative it is hard to say that I worked solely on these things because there was a lot back and forth between team members. Here I tried to present what I mostly worked on.
I went through
- Compiling research and talking to patients
- Making personas in collaboration with Isabel
- Creating User Journey as is and after Careo
- Comparing Personas
- Wireframing and sketching ideas
- Multiple rounds of prototyping
- Scenario video creation
Output- Scenario Video
Jean receives a notification from Careo, her health app, reminding her that she has an appointment with a sleep specialist in a few days. She clicks on the notification to review the appointment details and her data insight dashboard.
Seeing someone close who has undiagnosed chronic condition move from doctor to doctor without any successful diagnoses is heart-wrenching. Initially our class went through drills to closely understand ML/AI technology specifically IBM Watson's ML capabilities in healthcare. It was through published research and talking to a number of patients we knew with chronic illness, that in a group of three- Isabel, Maddy, and I decided to utilize our position as a designers to create something for patients with multiple chronic illness using machine learning capabilities.
Who, Why, What? We went through multiple rounds of research, talking to users, and feedback from some technologists @IBM before finalizing our topic.
Research Question
How might a design harness machine learning capabilities to enable a patient with chronic conditions to translate, prioritize, and analyze their data into a useful and understandable format — prior to a doctor’s visit?
Jean is a 20 year old college student suffering from multiple conditions like fatigue, asthma, joint pains, and sometimes stomach aches. She has to visit multiple specialists for her symptoms which haven’t been properly diagnosed.
Endorsements
"Syashi is a joy to work with—dedicated, thoughtful, innovative. While in grad school, she led a team to design a fantastic healthcare data platform in collaboration with IBM. From day one, Syashi's interest in A.I. informed her work. She thought deeply about how interfaces might leverage A.I. affordances to benefit users in a variety of scenarios from healthcare to creative practice. I highly recommend her!"
-Professor and Director, Master of Graphic & Experience Design, at NC State University.
PROCESS WORK
Initial Wireframing and Prototyping
Went through storyboarding and sketching phase for the initial. Maddy did most of the story boards. For wireframe sketching presented here are all my sketches:-
Prototyping- I worked on these initial iterations and then for the final versions worked together with Isabel.
