This GitHub repository contains an implementation of a malware classification/detection system using Convolutional Neural Networks (CNNs).

Prediction of Benign or Malignant Cancer Tumors

Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks

Semi-automatic Segmentation and Classification of Cell Clusters in a Pleural Effusion

The ML-based Breast Cancer Prediction Model classifies breast tumors as benign or malignant by analyzing key medical features from biopsy data. It offers healthcare professionals a reliable tool for diagnosis and treatment, showcasing the power of AI in healthcare with a focus on precision in detecting malignant tumors to improve patient outcomes.

Breast Cancer Detection using Machine Learning

I have created a classifier to classify website, whether it is benign or Malicious with using the CRISP DM concepts in it. Additionally I wrote blog on it https://medium.com/@prashantjadiya/process-of-classifying-malicious-and-benign-websites-815cc2b42435.

Breast Cancer Classification using CNN

Polyp-Classification-using-CNN

Designing an Image Classification Algorithm to classify an Image Patch into Malignant and Benign.

We use SVM (Support Vector Machines) to build and train a model using human cell records, and classify cells to whether the samples are benign or malignant.

Code for classification of cancerous vs. benign oral lesions using machine learning

A modular, scalable, deep learning-based pipeline for classifying mammographic images using various pre-trained CNN architectures.

This machine learning model classifies breast tumors as benign or malignant by analyzing medical features from biopsy data. It serves as a diagnostic support tool for healthcare professionals, helping improve cancer detection accuracy and patient care through AI-driven tumor classification.