R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.

Deep Learning Model that classifies brain tumor from images

Classification of brain tumor in MR images using deep spatiospatial models.

Tumor type classification with traditional feature extractions and classifiers.

Deep Learning for Classification of Bone Lesions on Routine MRI

The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations

Topological data analysis (TDA) in medical image analysis

In this we trained a model to detect if there is a tumor in the brain image given to the model. Meaning a model for binary class with an accuracy of above 90 for same and cross validation.

Use deep learning to identify ocular tumor types

Classification of Brain tumor

scMalignantFinder is a Python package specially designed for analyzing cancer single-cell RNA-seq datasets to distinguish malignant cells from their normal counterparts.

Using Naive Bayes for tumor classification in medical images. Great for healthcare & data science. Python & scikit-learn powered

Tumor Identification Based on Machine Learning Analysis of Gene Expression (2024)

Brain tumor classification based on MGMT methylation status present on the tumor cell.

Principal Component Analysis and Support Vector Machine for tumor classification in patients from the original Wisconsin breast cancer database.

Tumor Prediction Web App

An attempt to build accurate models for detecting various brain diseases

[a.a. 22/23] G. Antonucci, N. Pagliara

As part of the Thesis project, an Artificial Intelligence model was trained to classify breast tumors from ultrasound images as benign or malignant. Additionally, a user-friendly web application was created with Python for the backend and ReactJS for the frontend.