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README.md

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 # Breast Cancer Wisconsin v1.0 Model Card
 
-Abstract: This study explores the application of artificial intelligence (AI) in detecting breast cancer using the Wisconsin Breast Cancer dataset. Machine learning algorithms are trained on clinical and diagnostic features extracted from breast tissue samples to classify them as benign or malignant. Results demonstrate the effectiveness of AI-based approaches in accurately identifying breast cancer, offering potential improvements in early detection and treatment outcomes.
+This study explores the application of artificial intelligence (AI) in detecting breast cancer using the Wisconsin Breast Cancer dataset. Machine learning algorithms are trained on clinical and diagnostic features extracted from breast tissue samples to classify them as benign or malignant. Results demonstrate the effectiveness of AI-based approaches in accurately identifying breast cancer, offering potential improvements in early detection and treatment outcomes.
 
-Keywords: Breast Cancer, Artificial Intelligence, Machine Learning, Diagnosis
+Below is a visualization:
 
 ![examples](https://huggingface.co/anezatra/breast-cancer-wisconsin/raw/main/img.jpg)
 
-Developed By Anezatra Katedram
+A machine learning classifier trained on the breast cancer dataset can assist in diagnosing breast cancer by analyzing various features of the breast tissue. This classifier goes through a process of data collection, preprocessing, and training. Firstly, relevant data regarding patients' breast tissue characteristics, such as cell size, shape, and other diagnostic measurements, are collected. After that, the collected data undergo preprocessing steps, which may include handling missing values, normalization, and feature extraction. Once the data is prepared, it is used to train a machine learning model, such as a neural network or a support vector machine (SVM). During the training phase, the model learns the patterns and relationships within the data to classify breast tissue samples as malignant or benign accurately. Finally, the trained model can be deployed to predict whether a new tissue sample is indicative of cancer, providing valuable assistance to medical professionals in early detection and diagnosis.
+
+### Model Description
+
+- **Developed by:** Anezatra Katedram
+- **Model type:** Text Classification
+- **License:** GNU General Public License v3.0
+  - This model was trained by Anezatra and designed with the keras module.
+  - Use of the model for any commercial purpose requires agreement. [Contact TR](https://instagram.com/xx___xxbora_anezatraxx___xx_) for more information. 
+
+- **Model Description:** Breast Cancer Detection Using Artificial Intelligence (Trained with Keras module)
+- **BCWMAI:** Resources for more information: [Breast Cancer Wiconsin AI]