One, data security
Medical data involves the privacy aspects of personal data, so special attention should be paid to the protection of personal data privacy, China's "Network Security Law" provides that ? Network operators shall not disclose, tamper with, or destroy the personal information they collect; and shall not provide personal information to others without the consent of the person from whom it was collected. But after processing can not identify a specific individual and can not be recovered except?
While AI medical companies are required to process data in a way that does not identify a specific individual when using the data, which to a certain extent can help AI medical companies avoid data security issues, it still can't completely avoid data security issues.
Second, the data openness is limited
China's healthcare data openness is limited, which is mainly reflected in two aspects: the first is the restriction of the circulation between inside and outside the country, and the second is the restriction of the circulation between hospitals and hospitals or between hospitals and companies.
The restriction between within and outside China is actually quite simple, and this is regulated in each country, and some countries have more stringent regulations, such as the United States and Europe. In terms of hospital-to-hospital circulation restrictions, most of China's hospital data exists independently, circulation is relatively difficult, not to mention **** enjoy and data cross-application and data realization.
Third, the difference in data standards
China's large population, rich in medical data, but ? Data is big ? is not the same as ? big data? , clinical data is not uniform and standardized enough, the data between different regions and different hospitals have not established a link, and there is no unified standard, so the value is not reflected.
Four, ethical controversies
Despite the impressive progress made by AI in the healthcare industry, it is undeniable that there are still a series of ethical issues in the application of AI, such as: AI has caused the leakage of personal information, resulting in medical accidents, who is the responsible party?AI use The use of AI has caused the unemployment of medical personnel, triggering the transformation of the structure of the medical industry, how should society respond? There are a lot of questions that need to be faced and solved by industry practitioners.
Fifth, the high cost of data
All AI-based medical technology is based on ? data? based, the current AI medical company to obtain data channels are divided into three: first, with the hospital cooperation research projects; second, download data from the public dataset; third, buy data.
Overall, the cost of acquiring data is mainly in data acquisition and data labeling, and with the gradual deepening of the model training, the data throughput may be a geometric progression, and the cost will rise, which invariably increases the burden of realizing big data healthcare.
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