IntegrativeVAEs
Data integration network
Designs and builds neural networks to integrate diverse cancer patient data types for accurate diagnosis and clinical applications.
Variational autoencoders for cancer data integration
27 stars
5 watching
11 forks
Language: Python
last commit: over 3 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
| Develops an automatic prediction model for breast cancer proliferation scores from whole-slide histopathology images using deep learning techniques. | 207 |
| A tool for integrating and analyzing high-dimensional biological data using partial least squares regression | 32 |
| A tool for integrating multi-omics data from single cell sequencing technologies to improve analysis accuracy and discovery of biological patterns. | 34 |
| A generative model with tractable likelihood and easy sampling, allowing for efficient data generation. | 1,921 |
| Develops machine learning models to detect breast cancer from mammography images using deep learning techniques | 378 |
| Enables efficient and scalable exchange of data between different neuronal network modeling approaches | 55 |
| Tools for integrating multi-omics data to prioritize cancer genes | 15 |
| A platform for managing medical image data and metadata. | 450 |
| Improves performance of vision language tasks by integrating computer vision capabilities into large language models | 314 |
| This project uses CNNs to segment breast cancer lesions from medical images. | 75 |
| A convolutional neural network architecture for biomedical image segmentation | 430 |
| A framework for building applications with Large Language Models at the core using differentiable and classical programming | 997 |
| Investigating neural networks for drug discovery using multiple chemical descriptors. | 3 |
| A Python-based deep learning model for breast cancer classification from mammography images | 849 |
| Develops a method to learn shared latent structure between biomedical images and gene expression data | 25 |