Deep learning in the use of chest X-rays to predict disease

Want to analyze a chest X-ray with an intelligent algorithm? A group of researchers in the United States have recently made a very useful exploration in this area, which may be of great help to the future application and popularity.

Researchers at the National Institutes of Health in Bethesda (City of Central Maryland) have developed a deep learning-based algorithmic framework for detecting disease from chest X-rays. After the test is completed, the system will provide detailed instructions under the X-ray photograph so that the doctor can show the patient and detect the dangerous diseases earlier.

The team used NVIDIA's CUDA (Unified Computing Device Architecture) programming model and used the GPU to run and enhance their algorithms that help the algorithm locate the disease and describe its current location, severity, and lesions. The size and influence of the organ and other states. The reason why the GPU is used for calculation is because the GPU works very well with the features required by the deep learning program: the execution of commands is very efficient, and can undertake a huge amount of parallel computing, which allows the program to start a large number of analysis processes at the same time. Speed ​​up learning.

Let deep learning learn to identify medical picture information

Image information recognition has made great progress after the deep learning method has been improved. But most of the current programs are using publicly available images to train neural networks that can mark "natural" images, such as pets, natural landscapes, or urban landmarks - but without medical treatment. Picture of.

Because compared to the database of medical pictures with detailed annotations, it is difficult to obtain, and it is obviously impossible to publicly collect X-ray information. And the average person can clearly mark the tree, animals and buildings from the pictures. However, the identification of cardiopulmonary diseases such as cardiac hypertrophy or calcified granuloma requires professional knowledge.

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