Author: Zen and the Art of Computer Programming
With the rapid development of the Internet, the degree of informatization in modern society is getting higher and higher, and all walks of life are constantly transforming to digitalization. Artificial intelligence (AI) is closely related to the healthcare industry, and its application scenarios are rich and varied. However, how to better use artificial intelligence technology to process healthcare data and improve the quality of medical services is also one of the difficulties in the current healthcare field. The combination of artificial intelligence and the healthcare industry is a big deal for both doctors and patients. With the support of science and technology, we can provide doctors and patients with better and more practical diagnosis and treatment services, and help hospitals achieve the goal of "safely treating diseases and saving lives". Therefore, using artificial intelligence technology to process healthcare data has become an important direction to solve this problem.
2. Explanation of basic concepts and terms
Before entering the discussion of the article, you need to understand some basic concepts and terminology. 2.1 Data classification Healthcare data mainly includes the following categories:
1) Biological product data: including body organ slices, skin samples, chest X-rays, etc., used to assist doctors in diagnosis; 2) Imaging data: including X-ray images, CT scan images, MRI scan images, etc., which can directly observe the tissue structure and nervous system status of patients; 3) Text data: including medical records, test reports, nursing records, etc., usually written by patients, doctors or nurses and reviewed and confirmed; 4) Behavioral data: including patient activity records, risk factor identification, diagnosis willingness, etc., to assist doctors in diagnosis; Environmental data: including climate, weather, air pollution, noise, light, temperature, humidity, etc., which have a greater impact on patients and health conditions.
In addition to the above types of data, there are many other data types that also participate in the healthcare process. There are often multiple versions of these data, and there may be conflicts between data produced in different periods. This requires a unified platform to model the relationship between different data, and make predictions based on these models to improve diagnostic accuracy.
2.2 Artificial Intelligence (AI) Artificial Intelligence (Artificial Intelligence)