Xie Guotong, Chen Tiange, Li Yingxue, Chen Tingyu, Li Xiang, Liu Zhihong
Ping An Healthcare Technology, Beijing, China.
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.
Kidney Dis (Basel). 2020 Jan;6(1):1-6. doi: 10.1159/000504600. Epub 2019 Dec 3.
Artificial intelligence (AI) now plays a critical role in almost every area of our daily lives and academic disciplines due to the growth of computing power, advances in methods and techniques, and the explosion of the amount of data; medicine is not an exception. Rather than replacing clinicians, AI is augmenting the intelligence of clinicians in diagnosis, prognosis, and treatment decisions.
Kidney disease is a substantial medical and public health burden globally, with both acute kidney injury and chronic kidney disease bringing about high morbidity and mortality as well as a huge economic burden. Even though the existing research and applied works have made certain contributions to more accurate prediction and better understanding of histologic pathology, there is a lot more work to be done and problems to solve.
AI applications of diagnostics and prognostics for high-prevalence and high-morbidity types of nephropathy in medical-resource-inadequate areas need special attention; high-volume and high-quality data need to be collected and prepared; a consensus on ethics and safety in the use of AI technologies needs to be built.
由于计算能力的增长、方法和技术的进步以及数据量的爆炸式增长,人工智能(AI)如今在我们日常生活和学术学科的几乎每个领域都发挥着关键作用;医学也不例外。人工智能并非取代临床医生,而是在诊断、预后和治疗决策方面增强临床医生的智能。
肾病是全球重大的医学和公共卫生负担,急性肾损伤和慢性肾病都带来了高发病率和死亡率以及巨大的经济负担。尽管现有研究和应用工作为更准确的预测和对组织病理学的更好理解做出了一定贡献,但仍有许多工作要做和问题要解决。
在医疗资源不足的地区,针对高流行率和高发病率的肾病类型进行诊断和预后的人工智能应用需要特别关注;需要收集和准备大量高质量数据;需要就人工智能技术使用中的伦理和安全达成共识。