no code implementations • 5 Jun 2022 • Moumita Bhattacharya, Sudarshan Lamkhede
We motivate the need for recommendation systems that can cater to the members in-the-moment intent by leveraging their interactions from the current session.
no code implementations • 19 Sep 2021 • Moumita Bhattacharya, Dai-Yin Lu, Shibani M Kudchadkar, Gabriela Villarreal Greenland, Prasanth Lingamaneni, Celia P Corona-Villalobos, Yufan Guan, Joseph E Marine, Jeffrey E Olgin, Stefan Zimmerman, Theodore P Abraham, Hagit Shatkay, Maria Roselle Abraham
We assessed whether data-driven machine learning methods that consider a wider range of variables can effectively identify HC patients with ventricular arrhythmias (VAr) that lead to SCD.
no code implementations • 19 Sep 2021 • Moumita Bhattacharya, Dai-Yin Lu, Ioannis Ventoulis, Gabriela V. Greenland, Hulya Yalcin, Yufan Guan, Joseph E. Marine, Jeffrey E. Olgin, Stefan L. Zimmerman, Theodore P. Abraham, M. Roselle Abraham, Hagit Shatkay
Specifically, an ensemble of logistic regression and naive Bayes classifiers, trained based on the 18 variables and corrected for data imbalance, proved most effective for separating AF from No-AF cases (sensitivity = 0. 74, specificity = 0. 70, C-index = 0. 80).
no code implementations • 19 Sep 2021 • Moumita Bhattacharya, Claudine Jurkovitz, Hagit Shatkay
Unlike most prior work on topic modeling, we apply the method to codes rather than to natural language.
no code implementations • 17 Nov 2017 • Moumita Bhattacharya, Claudine Jurkovitz, Hagit Shatkay
In our study, we adapt the LDA model to identify latent topics in patients' EMRs.
no code implementations • 16 Aug 2017 • Moumita Bhattacharya, Deborah Ehrenthal, Hagit Shatkay
Obesity is one of the leading health concerns in the United States.