Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features ...
Brillouin imaging relies on the reliable extraction of subtle spectral information from hyperspectral datasets. To date, the mainstream practice has been to use line fitting of spectral features to retrieve the average peak shift and linewidth parame...
Neural networks : the official journal of the International Neural Network Society
Mar 26, 2021
Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while labels are only available in the source domain. Lots of works in UDA focus on finding a common representation of the two domains via domain alignment, assuming th...
Person reidentification (Re-ID) aims to match observations of individuals across multiple nonoverlapping camera views. Recently, metric learning-based methods have played important roles in addressing this task. However, metrics are mostly learned in...
With the rapid advances of various single-cell technologies, an increasing number of single-cell datasets are being generated, and the computational tools for aligning the datasets which make subsequent integration or meta-analysis possible have beco...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 11, 2021
We developed a fast and accurate deep learning approach employing a semi-unsupervised learning system (SULS) for capturing the real-time noisy, sparse, and ambiguous images of platelet activation. Outperforming several leading supervised learning met...
: In the current pandemic scenario, data mining tools are fundamental to evaluate the measures adopted to contain the spread of COVID-19. In this study, unsupervised neural networks of the Self-Organizing Maps (SOM) type were used to assess the spati...
Neural networks : the official journal of the International Neural Network Society
Feb 25, 2021
Unsupervised anomaly discovery in stream data is a research topic with many practical applications. However, in many cases, it is not easy to collect enough training data with labeled anomalies for supervised learning of an anomaly detector in order ...
BACKGROUND: During the COVID-19 pandemic in Canada, Prime Minister Justin Trudeau provided updates on the novel coronavirus and the government's responses to the pandemic in his daily briefings from March 13 to May 22, 2020, delivered on the official...
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