تقرير
Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data
| العنوان: | Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data |
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| المؤلفون: | Inglese, Paolo, Alexander, James L., Mroz, Anna, Takats, Zoltan, Glen, Robert |
| سنة النشر: | 2017 |
| المجموعة: | Computer Science Quantitative Biology Statistics |
| مصطلحات موضوعية: | Quantitative Biology - Quantitative Methods, Computer Science - Learning, Statistics - Machine Learning |
| الوصف: | The paper presents the application of Variational Autoencoders (VAE) for data dimensionality reduction and explorative analysis of mass spectrometry imaging data (MSI). The results confirm that VAEs are capable of detecting the patterns associated with the different tissue sub-types with performance than standard approaches. Comment: mass spectrometry imaging, variational autoencoder, desorption electrospray ionization, desi |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1708.07012 |
| رقم الأكسشن: | edsarx.1708.07012 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |