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pneumonia-classification

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This project uses a pre-trained ResNet50 model from the FastAI library to detect pneumonia in chest X-rays. The dataset which is available on kaggle is used for training the model which classifies the chest xray as NORMAL, VIRAL or BACTERIAL and this project is deployed on Flask

  • Updated Jan 2, 2024
  • Jupyter Notebook
HealthVision

This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.

  • Updated Apr 28, 2023
  • Python

This project uses a deep learning model built with the TensorFlow Library to detect pneumonia in X-ray images. The model architecture is based on the EfficientNetB7 model, which has achieved an accuracy of approximately 97.12% (97.11538%) on our test data. This high accuracy rate is one of the strengths of our AI model.

  • Updated May 4, 2024
  • Jupyter Notebook

Linear Regression , Cross Validation, k-mean clustering , Watershed , Gradients and Edge Detection , threshold , Correlation , Neural Network, Conventional Neural Network , Pneumonia Classification, Social Distancing, Rainfall Prediction, Boston Housing Price Prediction.

  • Updated Oct 5, 2020
  • Python

Бинарная классификация рентгеновских снимков грудной клетки. Определение наличия пневмонии у пациентов при помощи различных CNN архитектур. Использование метода Transfer Learning

  • Updated May 21, 2023
  • Jupyter Notebook

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