Reshape
Far far away, behind the word mountains, far from the countries.
Chest X-Ray Medical Diagnosis
Project Date
April 26, 2023
Role
Team lead, AI , Deep learning
Location
SR unioversity
Visit
https:///
The Chest X-Ray Medical Diagnosis project utilizes deep learning to assist in the automatic diagnosis of medical conditions from chest X-ray images. The goal was to leverage pre-trained Convolutional Neural Networks (CNN) to identify and classify different diseases, providing reliable assistance to healthcare professionals in medical diagnostics. This project involved the implementation of advanced image preprocessing, model training with large datasets, and the integration of Grad-CAM visualization techniques for interpretable AI.
Challenges: The primary challenge in this project was achieving high accuracy in diagnosing multiple diseases with limited labeled data. Advanced data augmentation techniques were applied to expand the dataset, and transfer learning was utilized to improve model performance without needing extensive training times. Additionally, providing explainability in the form of Grad-CAM visualizations helped in building trust and transparency in the model’s predictions, highlighting the key areas of the X-ray image used to make its diagnosis.
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Outcome: The deep learning model achieved an accuracy of [Insert Accuracy]% on the test dataset. The use of Grad-CAM heatmaps made the model’s predictions more interpretable, aiding healthcare professionals in better understanding and trusting the results. The solution has the potential to improve diagnostic efficiency and accuracy in clinical settings.
