Multilayer recursive feature elimination based on embedded genetic algorithm for cancer classification

A PyTorch implementation of MedSegDiff, a diffusion probabilistic model designed for medical image segmentation.

Predict which cell is cancerous with 96% accuracy using SVM machine learning algorithm.

(MIDL 2023) Code for "Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images"

BSc thesis: "Convolutional Neural Networks and their Application in Cancer Diagnosis based on RNA-Sequencing"

Classification of HAM10000 dataset using Pytorch and densenet

Taşınabilir Cihazlarda Gerçek Zamanlı Kanser Tespiti ve Sınıflandırmasını Yapan Uygulama

Creating a logistic regression algorithm without using a library and making cancer classification with this algorithm model (Kaggle Explained)

Malignancy classification using simple deep learning method in LIDC-IDRI dataset.

In this part, we developed an interface for Skin Cancer Classification using the Tkinter library in Python.

Code for: Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble Manner -- [IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB 24)]

Glioblasted is a machine learning model to assist in the detection of glioblastoma multiforme, a high-grade, aggressive form of central nervous system cancer.

Developed a fine-tuned EfficientNetB0 model which is a pre-trained Convolutional Neural Network (CNN) model to train using lungs and colon cancer dataset and classify if the unseen image belonged to benign, adenocarcinoma or squamous cell carcinoma cancer type.

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

Breast Cancer Prediction: Machine Learning-based Diagnosis with Streamlit

Criação de Rede Neural Multilayer Perceptron capaz de classificar corretamente casos de câncer de mama

Skin Cancer Classification

Adeno Carcinoma Cancer Classification

Prediction of Cancer Using Machine Learning Model

Bioinformatics project analyzing cancer metabolism using computational modeling and analysis. The project was awarded the GIDI-UP: Summer Research Award and includes data, models, and scripts.