Breast-Cancer-Detection-Model-By-using-Deep-Learning

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

This CNN is capable of diagnosing breast cancer from an eosin stained image. This model was trained using 400 images. It has an accuracy of 80%

This project is made in Matlab Platform and it detects whether a person has cancer or not by taking into account his/her mammogram.

ONCO is a cancer diagnosis/prognosis mobile application focused on the 3 main cancers of the thoracic region (Breast, Lung & Skin)

Pluralistic Image Completion for Anomaly Detection (Med. Image Anal. 2023)

Self-Supervised Vision Transformers for Breast Histopathology Image Embeddings in Invasive Ductal Carcinoma Detection

Breast Cancer Prediction using CNN

Add better insight into the use of AutoML for certain datasets, especially Breast Cancer Wisconsin (Diagnostic). In addition, it is expected to provide an understanding of the weaknesses and shortcomings of the selected use of AutoML, namely the Tree-Based Pipeline Optimization Tool (TPOT) for modeling automation.

This project is based on the dataset published by UCI MACHINE LEARNING available in Kaggle. The hottest project based on this dataset is developed by BUDDHINI W which has achieved an excellent acccuracy about 94.4% which looks perfect. However, in this repository, you can gain the accuracy of 99.1% on test data split.

Breast cancer prediction both in classification and clustering method for better understanding the data. Though clustering is different from classification,to finding the key aspect the data have,sometimes we need every possible way to catch behavior of the data.