51 Repositories
Python cancer-genomics Libraries
This repository contains all the data analytics projects that I've worked on in python.
93_Python_Data_Analytics_Projects This repository contains all the data analytics projects that I've worked on in python. No. Name 01 001_Cervical_Can
🧬 Non-linear feature reduction using Deep Autoencoders and Breast Cancer classification.
Project summary This repository contains the implementation of my bachelor degree project. The aim of the project is to apply non-linear feature reduc
Contextual Attention Network: Transformer Meets U-Net
Contextual Attention Network: Transformer Meets U-Net Contexual attention network for medical image segmentation with state of the art results on skin
Using deep learning model to detect breast cancer.
Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas
This is my research project for the Irving Center for Cancer Dynamics/Azizi Lab, Columbia University.
bayesian_uncertainty This is my research project for the Irving Center for Cancer Dynamics/Azizi Lab, Columbia University. In this project I build a s
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis Pretrained Models In this work, we created synthetic tissue
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
Evaluate on three different ML model for feature selection using Breast cancer data.
Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.
Breast cancer is been classified into benign tumour and malignant tumour.
Breast cancer is been classified into benign tumour and malignant tumour. Logistic regression is applied in this model.
Breast Cancer Classification Model is applied on a different dataset
Breast Cancer Classification Model is applied on a different dataset
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms
Breast-Cancer-Prediction
Breast-Cancer-Prediction Trying to predict whether the cancer is benign or malignant using REGRESSION MODELS in Python. Team Members NAME ROLL-NUMBER
Melanoma Skin Cancer Detection using Convolutional Neural Networks and Transfer Learning🕵🏻♂️
This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.
CellRank's reproducibility repository.
CellRank's reproducibility repository We believe that reproducibility is key and have made it as simple as possible to reproduce our results. Please e
To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types
To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types, from a Database Taken From Dr. Wolberg reports his Clinic Cases.
Simulate genealogical trees and genomic sequence data using population genetic models
msprime msprime is a population genetics simulator based on tskit. Msprime can simulate random ancestral histories for a sample of individuals (consis
Easy genetic ancestry predictions in Python
ezancestry Easily visualize your direct-to-consumer genetics next to 2500+ samples from the 1000 genomes project. Evaluate the performance of a custom
Orbivator AI - To Determine which features of data (measurements) are most important for diagnosing breast cancer and find out if breast cancer occurs or not.
Orbivator_AI Breast Cancer Wisconsin (Diagnostic) GOAL To Determine which features of data (measurements) are most important for diagnosing breast can
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.
Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.
Breast Cancer Detection 🔬 ITI "AI_Pro" Graduation Project
BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features are extracted using the pre-trained CNN.
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Simple web browser to visualize HiC tracks
HiCBrowser : A simple web browser to visualize Hi-C and other genomic tracks Fidel Ramirez, José Villaveces, Vivek Bhardwaj Installation You can insta
Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes
Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can
Full Spectrum Bioinformatics - a free online text designed to introduce key topics in Bioinformatics using the Python
Full Spectrum Bioinformatics is a free online text designed to introduce key topics in Bioinformatics using the Python programming language. The text is written in interactive Jupyter Notebooks, which allow you to try out and modify example code and analyses.
Grammar of Scalable Linked Interactive Nucleotide Graphics
Gosling.js Gosling.js is a declarative grammar for interactive (epi)genomics visualization on the Web. ⚠️ Please be aware that the grammar of Gosling.
A declarative (epi)genomics visualization library for Python
gos is a declarative (epi)genomics visualization library for Python. It is built on top of the Gosling JSON specification, providing a simplified interface for authoring interactive genomic visualizations.
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides Project | This repo is the officia
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
CSAW-M This repository contains code for CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer. Source code for tr
Official implementation of the method ContIG, for self-supervised learning from medical imaging with genomics
ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics This is the code implementation of the paper "ContIG: Self-s
The first GANs-based omics-to-omics translation framework
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
Code for "Optimizing risk-based breast cancer screening policies with reinforcement learning"
Tempo: Optimizing risk-based breast cancer screening policies with reinforcement learning Introduction This repository was used to develop Tempo, as d
This code is for eCaReNet: explainable Cancer Relapse Prediction Network.
eCaReNet This code is for eCaReNet: explainable Cancer Relapse Prediction Network. (Towards Explainable End-to-End Prostate Cancer Relapse Prediction
The FIRST GANs-based omics-to-omics translation framework
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
A naive Bayes model for cancer classification using a set of documents
Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.
pyradiomics v3.0.1 Build Status Linux macOS Windows Radiomics feature extraction in Python This is an open-source python package for the extraction of
An open source recipe book from the awesome staff of Clinical Genomics
meatballs An open source recipe book from the awesome staff of Clinical Genomics.
Michael Vinyard's utilities
Install vintools To download this package from pypi: pip install vintools Install the development package To download and install the developmen
Map single-cell transcriptomes to copy number evolutionary trees.
Map single-cell transcriptomes to copy number evolutionary trees. Check out the tutorial for more information. Installation $ pip install scatrex SCA
Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE)
OG-SPACE Introduction Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE) is a computational framewo
Toolchest provides APIs for scientific and bioinformatic data analysis.
Toolchest Python Client Toolchest provides APIs for scientific and bioinformatic data analysis. It allows you to abstract away the costliness of runni
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2 Status in Breast Cancer
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2 Status in Breast Cancer A novel graph neural network (GNN) based model (termed SlideGraph+
GDBIGtools: A command line tools for GDBIG varaints browser
GDBIGtools: A command line tools for GDBIG varaints browser Introduction Born in Guangzhou Cohort Study Genome Research Database is based on thousands
Implementation detail for paper "Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet"
Multi-level-colonoscopy-malignant-tissue-detection-with-adversarial-CAC-UNet Implementation detail for our paper "Multi-level colonoscopy malignant ti
Cancer metastasis detection with neural conditional random field (NCRF)
NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network
DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the
Data intensive science for everyone.
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