no code implementations • 27 Jul 2021 • Jose Roberto Ayala Solares, Yajie Zhu, Abdelaali Hassaine, Shishir Rao, Yikuan Li, Mohammad Mamouei, Dexter Canoy, Kazem Rahimi, Gholamreza Salimi-Khorshidi
In this study, we aim to (1) train some of the most prominent disease embedding techniques on a comprehensive EHR data from 3. 1 million patients, (2) employ qualitative and quantitative evaluation techniques to assess these embeddings, and (3) provide pre-trained disease embeddings for transfer learning.
no code implementations • 23 Mar 2020 • Yikuan Li, Shishir Rao, Abdelaali Hassaine, Rema Ramakrishnan, Yajie Zhu, Dexter Canoy, Gholamreza Salimi-Khorshidi, Thomas Lukasiewicz, Kazem Rahimi
In this paper, we merge features of the deep Bayesian learning framework with deep kernel learning to leverage the strengths of both methods for more comprehensive uncertainty estimation.
1 code implementation • 22 Jul 2019 • Yikuan Li, Shishir Rao, Jose Roberto Ayala Solares, Abdelaali Hassaine, Dexter Canoy, Yajie Zhu, Kazem Rahimi, Gholamreza Salimi-Khorshidi
Today, despite decades of developments in medicine and the growing interest in precision healthcare, vast majority of diagnoses happen once patients begin to show noticeable signs of illness.
no code implementations • 19 Jul 2019 • Abdelaali Hassaine, Dexter Canoy, Jose Roberto Ayala Solares, Yajie Zhu, Shishir Rao, Yikuan Li, Mariagrazia Zottoli, Kazem Rahimi, Gholamreza Salimi-Khorshidi
Multimorbidity, or the presence of several medical conditions in the same individual, has been increasing in the population, both in absolute and relative terms.
no code implementations • 20 Mar 2019 • Yikuan Li, Yajie Zhu
Deep Bayesian neural network has aroused a great attention in recent years since it combines the benefits of deep neural network and probability theory.