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Gaussian Process Based Heteroscedastic Noise Modeling for Tumor Mutation Burden Prediction from Whole Slide Images

https://doi.org/10.1101/554261
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-540-39857-8_42openalex-snapshot
A Two-Level Learning Method for Generalized Multi-instance Problems
inferredcites →https://doi.org/10.1007/s10618-013-0333-yopenalex-snapshot
Multiple instance learning via Gaussian processes
inferredcites →https://doi.org/10.1007/s10994-012-5283-xopenalex-snapshot
Bayesian multi-instance multi-label learning using Gaussian process prior
inferredcites →https://doi.org/10.1016/j.cell.2017.09.007openalex-snapshot
Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer
inferredcites →https://doi.org/10.1016/j.compmedimag.2018.01.008openalex-snapshot
Automated analysis and classification of melanocytic tumor on skin whole slide images
inferredcites →https://doi.org/10.1016/s0004-3702(96)00034-3openalex-snapshot
Solving the multiple instance problem with axis-parallel rectangles
inferredcites →https://doi.org/10.1017/s026988890999035xopenalex-snapshot
A review of multi-instance learning assumptions
inferredcites →https://doi.org/10.1038/s41591-018-0177-5openalex-snapshot
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
inferredcites →https://doi.org/10.1101/064279openalex-snapshot
H&E-stained Whole Slide Image Deep Learning Predicts SPOP Mutation State in Prostate Cancer
inferredcites →https://doi.org/10.1101/315648openalex-snapshot
Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies
inferredcites →https://doi.org/10.1101/gr.165985.113openalex-snapshot
Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival
inferredcites →https://doi.org/10.1109/cvpr.2016.266openalex-snapshot
Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.93openalex-snapshot
Variational Bayesian Multiple Instance Learning with Gaussian Processes
inferredcites →https://doi.org/10.1109/icdm.2009.82openalex-snapshot
Kernel Conditional Quantile Estimation via Reduction Revisited
inferredcites →https://doi.org/10.1109/tnnls.2017.2766164openalex-snapshot
Multiple-Instance Ordinal Regression
inferredcites →https://doi.org/10.1145/1961189.1961199openalex-snapshot
LIBSVM
inferredcites →https://doi.org/10.1158/1535-7163.mct-17-0386openalex-snapshot
Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers
inferredcites →https://doi.org/10.48550/arxiv.1407.0179openalex-snapshot
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
inferredcites →https://doi.org/10.48550/arxiv.1507.04513openalex-snapshot
Scalable Gaussian Process Classification via Expectation Propagation
inferredcites →https://doi.org/10.48550/arxiv.1802.04712openalex-snapshot
Attention-based Deep Multiple Instance Learning
inferredcites →https://doi.org/10.5244/c.30.71openalex-snapshot
Variational Weakly Supervised Gaussian Processes
inferredcites →https://doi.org/10.5555/1046920.1194909openalex-snapshot
A Unifying View of Sparse Approximate Gaussian Process Regression

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/path.5898openalex-snapshot
Artificial intelligence to identify genetic alterations in conventional histopathology
inferred← citeshttps://doi.org/10.1002/widm.1410openalex-snapshot
A 2021 update on cancer image analytics with deep learning
inferred← citeshttps://doi.org/10.1101/2022.09.25.509381openalex-snapshot
Identifying Genes with Location Dependent Noise Variance in Spatial Transcriptomics Data
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