Alice Rueda — accepted AI-conference papers

2023

Digital Phenotype Representation by Statistical, Information Theory, Data-Driven Approach with Digital Health Data

Binh P. Nguyen, Michael Nigro, Alice Rueda, Venkat Bhat, Sridhar Krishnan

ICASSP 2023accepted

Digital phenotyping (DP) is a multidisciplinary field of science that quantifies the individual level phenotype through active and passive data. Although DP is a multidisciplinary field, there lacks a technical and a systematic approach to representing DP. This work proposes the development of digit…

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2019

Augmenting Dysphonia Voice Using Fourier-based Synchrosqueezing Transform for a CNN Classifier

Alice Rueda, Sridhar Krishnan

ICASSP 2019accepted

The challenge of dysphonia voice studies is always the small dataset. It is difficult to apply more sophisticated deep learning techniques without overfitting or underfitting. Convolutional neural network (CNN) is a powerful classifier that requires a large amount of training data. Data augmentation…

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