人工智能决策系统在烧伤领域应用的主要瓶颈与解决途径

Main bottlenecks and solutions of artificial intelligence decision system in burn field

人工智能决策进入临床应用面临着3个瓶颈:烧伤医疗大数据、深度学习和医学伦理。如何在较长时间采集过程中保持数据稳定并选取科学方法加以分析与评判;机器人深度学习,学习什么与分析什么、如何克服人工智能机器与医师培养的长期性差异;在大数据与人工智能迅速发展形势下伦理短板日益体现。解决这3个问题的主要途径:应主动与数据科学家共同搭建数据模型平台,并制定数据采纳基本线路图,与此同时,由全国烧伤委员会制定大数据及人工智能的伦理规则刻不容缓。

Artificial intelligence decision-making faces 3 bottlenecks before it goes into burn treatment:big data,deep learning and medical ethics.How to maintain data stabiliy in long-term acquisition and select scientific methods for analysis and judgement.Which kinds of material should be studied and analyzed by deeping learning.How to overcome the long-term difference between artificial intelligence machine and doctor training.Under the situation of rapid development of big data and artificial intelligence,the ethical shortcomings are increasingly reflected.The main way to solve the 3 problems is:the initiative to build a data model platform together with data scientists should be taken,and the basic circuit diagram of data adoption should be developed.Meanwhile,it is urgent for the national committee of burns to formulate the ethical rules of big data and artificial intelligence.