Drug Response Prediction
7 papers with code • 1 benchmarks • 1 datasets
GDSCv2
Most implemented papers
Variational Autoencoder for Anti-Cancer Drug Response Prediction
JIAQING-XIE/Machine-Learning-in-Genomes-Summer-Research-
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Additionally, we show that our model can generates effective drug compounds not previously used for specific cancer cell lines.
Learning Curves for Drug Response Prediction in Cancer Cell Lines
adpartin/dr-learning-curves
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In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training sizes for two of the datasets, whereas the mNN performs better at the higher range of training sizes.
ASGARD: A Single-cell Guided pipeline to Aid Repurposing of Drugs
Intercellular heterogeneity is a major obstacle to successful precision medicine.
Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images
Prediction performance of three unimodal NNs which use GE are compared to assess the contribution of data augmentation methods.
A Fair Experimental Comparison of Neural Network Architectures for Latent Representations of Multi-Omics for Drug Response Prediction
kramerlab/multi-omics_analysis
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One important parameter is the depth of integration: the point at which the latent representations are computed or merged, which can be either early, intermediate, or late.
Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms
This study introduced a Drug Response Prediction (DRP) framework with two main goals: 1) design a data processing pipeline to extract information from tabular clinical data, and then preprocess it for functional use, and 2) predict RA patient's responses to drugs and evaluate classification models' performance.
TransEDRP: Dual Transformer model with Edge Emdedded for Drug Respond Prediction
For the branch of cell lines genomics, we use the multi-headed attention mechanism to globally represent the genomics sequence.
