Although the data volume of medical imaging is not large and privacy must be considered, because it is a low-context related problem, it is an area where machine learning can play a big role.However, Shangzhizhi initially encountered the challenge of "insufficient data". Although it has accumulated about 2000~3000 ECG data for nearly seven years, it still belongs to "small batch data", which is not enough to achieve machine.
Learning model calculation, so the initial data processing accuracy is only 50%. Fortunately, Amazon SageMaker provides data resources and data scientists assistance, and then through data model conversion, the data owned by Shangzhiji is expanded whatsapp list by 10 times. Even if there are many ECG patterns, the accuracy can exceed 80%. Not only that, the expansion from the originally familiar medical images to the interpretation of abnormal ECGs seems to belong to the medical field, but the service design is very different.
Ding Weineng estimates that it may take 1-2 years to verify the service if the business is alone. However, because he can "throw" all AI-related resources and equipment to AWS, the field application can be completed in less than 6 weeks. Let Shangzhizhi be bolder and more willing to invest in innovation when developing new application services in the future. DSC00665 Photo Credit: The News Lens Brand Studio Senior managers look here! AWS helps you find "good questions for AI" Asking good questions is a must-have for all corporate executives who want to promote AI applications.