COVID-19 in differential diagnosis of online symptom assessments

no code implementations • 7 Aug 2020 • Anitha Kannan, Richard Chen, Vignesh Venkataraman, Geoffrey J. Tso, Xavier Amatriain

Traditional symptom checkers, however, are based on manually curated expert systems that are inflexible and hard to modify, especially in a quickly changing situation like the one we are facing today.

Open Set Medical Diagnosis

no code implementations • 7 Oct 2019 • Viraj Prabhu, Anitha Kannan, Geoffrey J. Tso, Namit Katariya, Manish Chablani, David Sontag, Xavier Amatriain

Machine-learned diagnosis models have shown promise as medical aides but are trained under a closed-set assumption, i. e. that models will only encounter conditions on which they have been trained.

Medical Diagnosis Open Set Learning

Learning from the experts: From expert systems to machine-learned diagnosis models

no code implementations • 21 Apr 2018 • Murali Ravuri, Anitha Kannan, Geoffrey J. Tso, Xavier Amatriain

In this paper, we present a method to merge both approaches by using expert systems as generative models that create simulated data on which models can be learned.

Medical Diagnosis