arXiv subjects

Jennifer Yu

Publications and source records attributed to Jennifer Yu.

3 recordsLinked to original sources

arXiv2023

The Cardiac Analytics and Innovation (CardiacAI) Data Repository: An Australian data resource for translational cardiovascular research

In Australia, cardiovascular diseases (CVD) are managed in a complex and fragmented healthcare system across multiple providers. A data repository that links data sources, and enables advanced analytics and big data technologies, will generate novel insights, and allow development of translational tools that can improve patient care and outcomes. The Cardiac Analytics and Innovation (CardiacAI) project has established a research-ready electronic medical records data resource to enable collaborative and translational cardiovascular research. The CardiacAI data repository prospectively extracts de-identified electronic medical record (EMR) data from two local health districts (LHD) in New South Wales (NSW), Australia. These data are linked with Australian population health data to ascertain longitudinal hospitalisation and death outcomes. The data are stored within a secure, cloud-based storage and analytics platform. The CardiacAI data repository is a not-for-profit data resource that promotes collaboration and responsible sharing of data. The CardiacAI data repository is a resource for Australian healthcare providers, clinicians and researchers seeking to improve cardiovascular care. The project is expanding to include data from stroke hospitalisations and two additional NSW LHDs, and is actively exploring linkage with ECG signal data, medical imaging data and community-based healthcare. The CardiacAI project has the potential to unlock a wealth of novel insights and translational tools that improve secondary prevention and treatment of CVD.

cs.DL↗

arXiv2022

Dynamic Interpretable Change Point Detection

Identifying change points (CPs) in a time series is crucial to guide better decision making across various fields like finance and healthcare and facilitating timely responses to potential risks or opportunities. Existing Change Point Detection (CPD) methods have a limitation in tracking changes in the joint distribution of multidimensional features. In addition, they fail to generalize effectively within the same time series as different types of CPs may require different detection methods. As the volume of multidimensional time series continues to grow, capturing various types of complex CPs such as changes in the correlation structure of the time-series features has become essential. To overcome the limitations of existing methods, we propose TiVaCPD, an approach that uses a Time-Varying Graphical Lasso (TVGL) to identify changes in correlation patterns between multidimensional features over time, and combines that with an aggregate Kernel Maximum Mean Discrepancy (MMD) test to identify changes in the underlying statistical distributions of dynamic time windows with varying length. The MMD and TVGL scores are combined using a novel ensemble method based on similarity measures leveraging the power of both statistical tests. We evaluate the performance of TiVaCPD in identifying and characterizing various types of CPs and show that our method outperforms current state-of-the-art methods in real-world CPD datasets. We further demonstrate that TiVaCPD scores characterize the type of CPs and facilitate interpretation of change dynamics, offering insights into real-life applications.

cs.LG↗

arXiv2001

The Optical/Infrared Astronomical Quality of High Atacama Sites. I. Preliminary Results of Optical Seeing

The region surrounding the Llano de Chajnantor, a high altitude plateau in the Atacama Desert in northern Chile, has caught the attention of the astronomical community for its potential as an observatory site. Combining high elevation and extremely low atmospheric water content, the Llano has been chosen as the future site of the Atacama Large Millimeter Array. We have initiated a campaign to investigate the astronomical potential of the region in the optical/infrared. Here, we report on an aspect of our campaign aimed at establishing a seeing benchmark to be used as a reference for future activities in the region. After a brief description of the region and its climate, we describe the results of an astronomical seeing campaign, carried out with a Differential Image Motion Monitor that operates at 0.5 micron wavelength. The seeing at the Llano level of 5000 m, measured over 7 nights in May 1998, yielded a median FWHM of 1.1". However, the seeing decreased to 0.7" at a modest 100 m gain above the plateau (Cerro Chico), as measured over 38 nights spread between July 1998 and October 2000. Neither of these represents the best seeing expected in the region; the set of measurements provides a reference base for simultaneous dual runs at Cerro Chico and at other sites of interest in the region, currently underway. A comparison between simultaneous measurements at Cerro Chico and Cerro Paranal indicates that seeing at Cerro Chico is about 12% better than at Paranal. The percentage of optically photometric nights in the Chajnantor region is about 60%, while that of nights useful for astronomical work is near 80%.

astro-ph↗