Peds AI — built by founder, chief scientist, and digital taquero, Christopher Loren Thompson, MD, MHI a pediatrician with a background in machine learning and medical informatics.
The company aims to use novel AI infrastructure to build safe, precision medicine tools for health research and low risk clinical tasks.
Dr. Thompson’s medical practice givens him specific insight into day-to-day clinical realities. He is ideally suited to provide you with statistical, theoretical and practical support for any research effort related to AI implementation; His epidemiological research has been published in JAMA Pediatrics.
Are you a researcher?
1) With Cognitron, you can explore new types of data collection.
With use of development services available on the Google and Amazon Cloud, we can design open-ended, adaptive surveys. Responses by participants can be captured via a combination of structured items (the traditional approach) or via open-ended, free-text responses with automated categorization.
2) Collect data more efficiently with natural language understanding.
While fixed-choice response items can be included in any workflow, natural language is fluid, fast and flexible in many circumstances. Applications include automated patient check-in linked to research study recruitment, and other data collection tasks.
3) Create a customized virtual agent that can interact with users or research participants.
Linking together natural language understanding, and risk assessment based on 1,000,000 health-focused surveys, a capable AI agent can profoundly change your research capabilities. Natural language processing and computation determine the next step. Conversations can be ‘supervised’ — monitored in real time by support staff.
4) Build a just-in-time-adaptive-intervention.
Using Google infrastructure and the Peds.AI front-end app, this kind of intervention can be rapidly developed. Importantly, tailoring variables can be determined by risk calculation from the National Survey of Drug Use and Health.