output
20152024
most citedDistilling Knowledge from Deep Networks with Applications to Healthcare Domain

112 citations

12 papers

cs.CY2024★ 1 cited

Behind the Smile: Mental Health Implications of Mother-Infant Interactions Revealed Through Smile Analysis

Adi Dust, Pat Levitt, Maja Matarić

Mothers of infants have specific demands in fostering emotional bonds with their children, characterized by dynamics that are different from adult-adult interactions, notably requi…

cs.HC2022

Evaluating Temporal Patterns in Applied Infant Affect Recognition

Allen Chang, Lauren Klein, Marcelo R. Rosales +3

Agents must monitor their partners' affective states continuously in order to understand and engage in social interactions. However, methods for evaluating affect recognition do no…

nucl-th2022★ 6 cited

Path Integral Quantum Monte Carlo Calculations of Light Nuclei

Rong Chen, Kevin E. Schmidt

We describe a path-integral ground-state quantum Monte Carlo method for light nuclei in continuous space. We show how to efficiently update and sample the paths with spin-isospin d…

cs.LG2019★ 41 cited

Interpreting a Recurrent Neural Network's Predictions of ICU Mortality Risk

Long V. Ho, Melissa D. Aczon, David Ledbetter +1

Deep learning has demonstrated success in many applications; however, their use in healthcare has been limited due to the lack of transparency into how they generate predictions. A…

eess.IV2018★ 5 cited

Multidimensional Correlation Spectroscopic Imaging of Exponential Decays: From Theoretical Principles to In Vivo Human Applications

Daeun Kim, Jessica L. Wisnowski, Christopher T. Nguyen +1

Multiexponential modeling of relaxation or diffusion MR signal decays is a popular approach for estimating and spatially mapping different microstructural tissue compartments. Whil…

q-bio.QM2018★ 6 cited

Quantifying the Sensitivity of HIV-1 Viral Entry to Receptor and Coreceptor Expression

Bhaven Mistry, Maria R. D'Orsogna, Nicholas E. Webb +2

Infection by many viruses begins with fusion of viral and cellular lipid membranes, followed by entry of viral contents into the target cell and ultimately, after many biochemical…

stat.ML2017★ 27 cited

The Dependence of Machine Learning on Electronic Medical Record Quality

Long Ho, David Ledbetter, Melissa Aczon +1

There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). Across different institutions, however, EMR quality can vary widely. This work i…

q-bio.GN2017★ 42 cited

Evidence-based gene models for structural and functional annotations of the oil palm genome

Chan Kuang Lim, Tatiana V. Tatarinova, Rozana Rosli +12

The advent of rapid and inexpensive DNA sequencing has led to an explosion of data waiting to be transformed into knowledge about genome organization and function. Gene prediction…

stat.ML2015★ 112 cited

Distilling Knowledge from Deep Networks with Applications to Healthcare Domain

Zhengping Che, Sanjay Purushotham, Robinder Khemani +1

Exponential growth in Electronic Healthcare Records (EHR) has resulted in new opportunities and urgent needs for discovery of meaningful data-driven representations and patterns of…

stat.ME2015

Nonparametric estimation of a mixing distribution for a family of linear stochastic dynamical systems

Alona Kryshchenko, Alan Schumitzky, Mike van Guilder +1

In this paper we develop a nonparametric maximum likelihood estimate of the mixing distribution of the parameters of a linear stochastic dynamical system. This includes, for exampl…

q-bio.PE2015

Genomic study of the Ket: a Paleo-Eskimo-related ethnic group with significant ancient North Eurasian ancestry

Pavel Flegontov, Piya Changmai, Anastassiya Zidkova +14

The Kets, an ethnic group in the Yenisei River basin, Russia, are considered the last nomadic hunter-gatherers of Siberia, and Ket language has no transparent affiliation with any…

q-bio.GN2015★ 33 cited

Differential Evolution Approach to Detect Recent Admixture

Konstantin Kozlov, Dmitry Chebotarov, Mehedi Hassan +4

The genetic structure of human populations is extraordinarily complex and of fundamental importance to studies of anthropology, evolution, and medicine. As increasingly many indivi…