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The primary use case for bone fracture detection using deep learning is to automatically and accurately identify fractures in medical imaging such as X-rays, CT scans, or MRIs. This model can assist radiologists and healthcare providers by providing a second opinion and highlighting potential fractures that might be missed during manual examination.
Benefits
Deep learning models enhance the accuracy and speed of fracture detection, reducing the likelihood of misdiagnosis and ensuring prompt treatment for patients. Additionally, these models can alleviate the workload of radiologists, allowing them to focus on more complex cases and improving overall healthcare efficiency.
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Feature Description
Detecting whether there is fracture in the bone surface or not through x-ray based image data using CNN model in deep learning.
propose solution will consist of complete EDA , feature engineering , data analysis , and a Streamlit based GUI application.
(I will also try to figure out other deep learning models like Resnet , Vgg16 , Inception )
https://www.kaggle.com/datasets/vuppalaadithyasairam/bone-fracture-detection-using-xrays
Use Case
The primary use case for bone fracture detection using deep learning is to automatically and accurately identify fractures in medical imaging such as X-rays, CT scans, or MRIs. This model can assist radiologists and healthcare providers by providing a second opinion and highlighting potential fractures that might be missed during manual examination.
Benefits
Deep learning models enhance the accuracy and speed of fracture detection, reducing the likelihood of misdiagnosis and ensuring prompt treatment for patients. Additionally, these models can alleviate the workload of radiologists, allowing them to focus on more complex cases and improving overall healthcare efficiency.
Add ScreenShots
None
Priority
High
Record
The text was updated successfully, but these errors were encountered: