Fracture Detection using Convolutional Neural Networks| Python| Techneons

This video presents the Python programming demonstration for fracture detection using Convolutional Neural Networks (CNN). Recently, artificial intelligence and machine learning algorithms are being used for classification where deep learning object detection networks can be trained to accurately detect the fractures that can help the orthopedics.

Using convolutional neural networks, our channel Techneons has trained a deep learning model that can detect the fractures on X-rays and developed a web based application from the CNN algorithm. Using Python programming, we have demonstrated that the ability to accurately detect fractures significantly improves when the orthopedic clinicians (or even the general public) are provided with the assistance of this trained deep learning model. This is therefore a very useful and reliable tool for the clinical industry that can limit the wrong decisions during diagnosis especially when there is a shortage of radiologists. This alogorithm can substantially improve the diagnosis results and thereby providing better patient care.

00:01 - Overview of fracture detection using CNN algorithm
00:23 - Deploying CNN algorithm into the application and html files
01:27 - Python Demonstration
02:04 - Application of conv2D filter and Tanh activation function
02:20 - Max pooling 2D function and sigmoid activation functions
03:16 - Building and saving the models
03:50 - Testing the application
04:18 - Classification results/fracture report generation

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