The goal of this research was to understand market, customer, and end user needs and translate them to technical requirements for AI medical imaging analytics solutions.
When I first approached this project as Lead UX Researcher, I began by engaging with radiologists and pathologists through 1:1 interviews to understand their workflows and learn where they wanted imaging analytics and artificial intelligence to influence their workflows. After conducting over 25 qualitative interviews and observations I conducted a content analysis of the data, created clinician journey maps, and reported findings on pain points, user needs, acceptance of AI, clinical use cases for AI in imaging, and opportunities for Intel in these areas.
In the next phase of this research I explored data administrator, CIO, CTO, and systems integrator thoughts on incorporating medical imaging analytics in their data centers. This research began with qualitative interviews which, combined with information we learned from the interviews with radiologists and pathologists, informed the creation of of a survey. The results of this survey along with the results from the qualitative interviews have been influential in the shaping of the medical imaging analytics offerings at Intel.
Role: Lead UX Researcher
•Designed, executed, and managed all UX research efforts for medical imaging analytics
•Utilized qualitative and quantitative data collection and analysis
•Analyzed existing market reports and peer reviewed journal articles
•Collaborated with team engineers to develop technical requirements based on UX research
•Deliverables: technical requirements, personas, workflow analysis, journey maps, white papers, journal publications, thought leadership, marketing collateral
•Solutions influenced: VNA/PACS modernization; deep learning training appliance, deep learning inferencing appliance