Appropriate intervention of AI can "relieve the pressure on the scene". Fourth, physicians can use the status of "expert endorsement" to make AI the best assistant in the auxiliary medical field. DSC00661 Chen Dizhi, Chief Strategy Officer of Shangzhizhi Photo Credit: The News Lens Brand Studio Because of these four characteristics, when the electrocardiogram data is immediately transmitted from the ambulance to the platform, the data is connected through Amazon SageMaker, and it is immediately determined who is the AMI patient, and then AWS will immediately transmit the abnormal data to the communication group. Personnel can then prepare for subsequent rescue procedures in advance.
When the ambulance staff no longer have to wait for the doctor to judge from a distance, and the medical staff no longer have to bear excessive pressure and constantly check whether there is an emergency message from the mobile phone, the medical scene whatsapp list can make good use of the precious time grabbed from the hands of God and concentrate more on the patient. Prepare for follow-up surgery. Medical AI is not easy to implement, machine learning can help The reason why we can grab time from God is machine learning.
Machine learning is good at solving problems that are "independent of the external context", that is, those problems that can be inferred only by judging a single or a few known kinds of data. Although the amount of data in medical imaging is not large, and privacy must be considered, because it is a low-context 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 is still "small batch data", which is not enough to achieve machine learning model calculation, so the initial data processing accuracy is only 50%.