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Contributor npj Digital Medicine

A step towards better sleep science: a large sleep-wake scoring benchmark

For many years, sleep-wake scoring algorithms were created and validated with small and private datasets with no more than one hundred participants. In this paper, we devised the largest dataset up to date for the sleep-wake classification problem and analyzed the performance of popular traditional algorithms as well as state-of-the-art machine learning techniques to tackle this problem. By making this dataset public, researchers can use our data and results as a benchmark to develop newer algorithms.
Go to the profile of Joao Palotti
Jun 07, 2019
Contributor npj Digital Medicine

How can AI modernize Veterinary Care?

When innovations are rapidly sweeping across all fields of human society, we want to leverage them to improve every aspect of our life and the lives around us --- the companion animals. Veterinary records can be extremely valuable for research and public health --- 60-70% of all emerging diagnoses are transmitted from animals to humans. Beyond that, companion animals have been increasingly used to study naturally occurring diseases as they share similar environments to humans and are often representative disease models to recapitulate diseases in humans.
Go to the profile of Allen Nie
May 08, 2019
Contributor npj Digital Medicine

Integrating laboratory tests for deep phenotyping and biomarker discovery

Clinical laboratory tests are one of the key components of electronic health records and contain rich patient phenotypic information. However, there are often multiple similar laboratory tests for the same medical issue, creating a data integration problem when being used for translational research. In our paper, we presented a novel approach that allows one to semantically integrate laboratory tests by mapping their results into Human Phenotype Ontology terms. The transformation generated detailed patient phenotypic profiles that can be used for biomarker screen.
Go to the profile of Aaron Zhang
May 02, 2019
Contributor npj Digital Medicine

A Mom's Motivation to Monitor Breathing

My team at UC Irvine has developed small Band-Aid© like sensors that can continuously monitor both respiration rate and volume. We made these disposable sensors with an inexpensive children’s toy, Shrinky-Dinks. Link to paper: DOI: 10.1038/s41746-019-0083-3
Go to the profile of Michelle Khine
Feb 13, 2019