Medical machine learning system
Disclosed is a medical equipment learning system which includes: a data extraction module configured to collect and then extract text-type data from medical data; a visualization module configured to generate image-type data as visualization data by using the text-type data extracted by the data extraction module; a pre-processing module configured to generate an input data set to execute equipment learning based on the visualization data; a learning module configured to execute equipment learning in the input data set generated by the pre-processing module; a prediction module configured to predict a disease when new image-type data is input based on the result learned in the learning module; and a storage module provided to store and check data of each module.
1. A medical machine learning system comprising:
a data extraction module configured to collect and then extract text-type data from medical data;
a visualization module configured to generate image-type data as visualization data by retrieving a previously stored medical information model which references the text-type data extracted by the data extraction module;
a pre-processing module configured to generate an input data set to execute machine learning based on the visualization data;
a learning module configured to execute machine learning in the input data set generated by the pre-processing module by using an algorithm including a support vector equipment, a convolutional neural network, or a generative adversarial neural network;
a prediction module configured to predict a disease when new image-type data is input based on a comparison with a result of the machine learning in the input data set in the learning module; and
a storage module provided to store and check data of each module,
wherein the data extraction module, the visualization module, the pre-processing module, the learning module, the prediction module, and the storage module are each implemented via at least one processor.
2. The medical machine learning system of claim 1 , wherein the image-type data generated by the visualization module is a predetermined 2D or 3D model.
3. The medical machine learning system of claim 1 , wherein the data extraction module collects the medical data by receiving materials from any one or more of a portable file, a hospital, a cloud server, and a personal device.
4. The medical machine learning system of claim 1 , wherein the visualization module expresses a name of a disease, a severity of the disease, a chronicity, a degree of malignancy, various test results, functional test results, and data results extracted from a machine by any one or more of colors, brightness or transparency, patterns, and textures of the visualization data.
5. The medical machine learning system of claim 1 , wherein the visualization module uses an image extracted from a medical image or an anatomical pathology photograph as a texture.
6. The medical machine learning system of claim 1 , wherein the visualization module uses one or more layers according to characteristics of the medical data.
7. The medical machine learning system of claim 1 , wherein the visualization module generates the image-type data by combining one or more medical information models.
8. The medical machine learning system of claim 1 , wherein the pre-processing module generates the input data set by normalizing various types of image-type data having different standards.
9. The medical machine learning system of claim 1 , wherein the visualization module further includes a medical information model expressing medical information which is not anatomically related inside and outside a body in a basic model.
10. The medical machine learning system of claim 1 , wherein the pre-processing module creates temporal data by combining several image-type data having different creation time points and generates the input data set according to a change in time.
11. The medical machine learning system of claim 1 , wherein the pre-processing module forms the input data set by selecting only a portion of an image-type data area.
12. The medical machine learning system of claim 1 , wherein the pre-processing module generates the input data set 2-dimensionally converted from the image-type data expressed 3-dimensionally.