Can AI doctors bring about a major transformation in medical models?

2023-06-20

Artificial intelligence has developed rapidly, and the recent emergence of ChatGPT-4 has once again sparked a wave of artificial intelligence. In the future, AI will become increasingly intelligent and its application scenarios will become more widespread. Every industry should face this reality, and perhaps many industries' jobs will be replaced by AI in the future. The medical process, as an empirical science, is based on common medical knowledge for different individual patients, supplemented by medical analysis of individual characteristics, in order to complete the process of diagnosis and treatment. Doctors can engage in medical work after learning and completing medical theoretical knowledge and completing sufficient medical training. The characteristics of doctors' growth process are very consistent with the training and application of artificial intelligence Big data model. The shortage of high-quality medical technology talents for artificial intelligence doctors is the most important factor restricting human health security, which is urgently needed in society. In China, the socio-economic development in different regions is imbalanced, and the level of medical resources and medical technology is also severely unbalanced in different regions. The medical and health security in developed areas is significantly better than that in remote areas, mainly due to the imbalance of medical resources, including medical equipment and technology. In recent years, China has given great support to the grass-roots medical system. The medical equipment at the grass-roots level and in remote areas has been significantly improved, which theoretically can fully meet the current needs of people's health security. However, in fact, the medical and health security at the grass-roots level and in remote areas is still far behind that in developed areas, which is due to the backward medical technology at the grass-roots level and in remote areas. The people in these areas need higher quality doctors to provide medical security, fundamentally solving a series of problems such as difficulty, high cost, and returning to poverty due to illness among grassroots and remote areas. Similarly, globally, there are many poor and underdeveloped countries and regions that need to improve their healthcare security systems, among which high-quality medical technicians are the most fundamental demand. However, the training cycle for doctors is long, and their energy and time are limited, resulting in significant limitations in their mastery of medical knowledge. If AI doctors can master massive medical Big data and get sufficient Big data model training, they can complete the disease diagnosis and treatment process with high quality, then the shortage of high-quality medical technology can be effectively alleviated. In addition, even in developed regions, there are still many medical accidents caused by misdiagnosis and mistreatment. This is because people's learning, storage, and application of medical knowledge are limited, and the amount and usage of knowledge vary from person to person. The subjectivity of doctors is like two sides of a coin, that is, they can analyze and diagnose patients based on their individual characteristics, but they can also ignore the objectivity of diseases due to their one-sided subjectivity, resulting in misdiagnosis and mistreatment. Fully trained artificial intelligence doctors can not only analyze the specific characteristics of different patients' diseases, but also strictly follow the principles of medical diagnosis and treatment, without being influenced by the doctor's emotions. In 2000, a survey conducted by the Institute of Medicine of the National Academy of Sciences of the United States showed that the error rate in some places decreased by 81% after using computers to write prescriptions. In 2019, the World Health Organization updated the "10 Facts of Patient Safety", one of which is that 4 out of every 10 patients are at the primary level

Edit:Hou Wenzhe    Responsible editor:WeiZe

Source:XinhuaNet

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