Demonstrator workflows for the SciPipe paper in GigaScience
-
Updated
Apr 9, 2021 - Go
Demonstrator workflows for the SciPipe paper in GigaScience
It creates machine learning model that predict whether the person will suffer from breast cancer or not.
Single-cell RNA-seq analysis of lung cancer (NSCLC) using Seurat, SingleR, and Monocle3. Includes QC, clustering, marker identification, pathway enrichment, and pseudotime analysis.
Data analysis project using Excel, Power BI & Tableau to visualize cancer risk and treatment cost.
Objective of this analysis is to classify the class variable into people who have surivived after operation and people who didn't surivive. We try to create a simple model, in order to classify the same.
A course project for estimating the parameters of a Weibull Distribution which models the survival rates of cancer using Maximum Likelihood Estimation
📄 Streamline your research with automated workflows for reading and summarizing top academic papers from HuggingFace and analyzing content from PDFs.
Add a description, image, and links to the cancer-analysis topic page so that developers can more easily learn about it.
To associate your repository with the cancer-analysis topic, visit your repo's landing page and select "manage topics."