Biologically informed deep neural networks provide quantitative ...

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of recurrent glioblastoma. This study addresses the ...

Biologically-informed deep neural networks provide quantitative ...

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma.

Biologically-informed deep neural networks provide quantitative ...

We develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules.

Biologically-informed deep neural networks provide quantitative ...

BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to ...

(PDF) Biologically informed deep neural networks provide ...

PDF | On Oct 19, 2024, Hairong Wang and others published Biologically informed deep neural networks provide quantitative assessment of ...

(PDF) Biologically-informed deep neural networks provide ...

BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to ...

A systematic review of biologically-informed deep learning models ...

This paper provides a systematic review focused on omics-based DL models used in cancer biology highlighting the dialogue and convergence ...

Biologically informed deep neural networks provide quantitative ...

Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma ... We developed BioNet, a ...

Biologically informed deep neural networks provide ... - Altmetric

Click here to find out more. Title. Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in ...

Biologically informed deep neural networks provide quantitative ...

Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. https://doi.org ...

MediFormatica on LinkedIn: Biologically informed deep neural ...

Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma ...

Interpreting biologically informed neural networks for enhanced ...

We present a deep learning approach to combine biological pathway analysis and biomarker identification to increase the interpretability of proteomics ...

Designing interpretable deep learning applications for functional ...

... provide insight in the biological ... 74. Elmarakeby. HA. ,. Hwang. J. ,. Arafeh. R . et al. . Biologically informed deep neural network for ...

A systematic review of biologically-informed deep learning models ...

Quantitative Biology > Quantitative Methods. arXiv:2207.00812 (q-bio) ... The paper provides a critical outlook into contemporary methods ...

Biologically-informed deep neural networks provide ... - X-MOL

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Biologically informed deep neural network for prostate cancer ...

Here we developed P-NET-a biologically informed deep learning model-to stratify patients with prostate cancer by treatment-resistance state and evaluate ...

Biologically-informed neural networks guide mechanistic modeling ...

Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the ...

Deep neural networks and image classification in biological vision

... network performance and the biological system using both quantitative and qualitative performance measures. ... informing theories of biological vision, networks ...

BioM2: biologically informed multi-stage machine learning for ...

2. Juan. H-F. ,. Huang. H-C . Quantitative analysis of high-throughput biological data ... et al. Biologically informed deep neural network for ...

arXiv:2207.00812v3 [q-bio.QM] 24 Jan 2023

... Neural. Networks (KPNNs) aiming at providing a biologically ... “Biologically informed deep neural network for prostate cancer discovery”.