DOOG-E is a generative healthcare AI that uses deep learning to predict future outcomes for individuals and populations, pre-trained on over a million patients' claims and clinical FHIR data.
DOOG-E (patent pending) can generate future paths for a patient, condition, procedure, or their combinations. Aggregated paths can probabilistically shed light on a patient or population's journey.
cohort definition(patient history includes)
femalemale patients
305070 year old
with strokecolon cancerheart failure
undergoing a physicalheart bypassknee replacement
DOOG-E(frequency of predictions over next year)
Risk calculation
DOOG-E can calculate the risk for how quickly a disease progresses for a patient or population.
cohort definition(patient history includes)
Male patients who are 67 years old with obesity with a treatment plan starting with
DOOG-E can identify futures impacted by medical decisions. The monetary impact of future events can be aggregated to understand the economics of a care decision.
cohort definition(patient history includes)
59 year old female with osteoarthritis for the hip who is
going in for a physicalhip replacement
DOOG-E(frequency of predictions over next year)
Quality measurement and readmissions
DOOG-E can can calculate the quality of care via readmissions or other events indicative of positive healthcare outcomes.
cohort definition(patient history includes)
71 year old female patient with congestive heart failure and a treatment plan beginning with the following:
a primary care appointmentfurosemideangiotensin receptor blocker (losartan)implantable cardiac defibrillator