Joslin Diabetes Centre, Beetham Eye Institute, Boston, MA, USA.
Department of Ophthalmology, Harvard Medical School, Boston, MA, USA.
Semin Ophthalmol. 2021 May 19;36(4):250-257. doi: 10.1080/08820538.2021.1893351. Epub 2021 Mar 18.
The goal of personalized diabetes eye care is to accurately predict in real-time the risk of diabetic retinopathy (DR) progression and visual loss. The use of electronic health records (EHR) provides a platform for artificial intelligence (AI) algorithms that predict DR progression to be incorporated into clinical decision-making. By implementing an algorithm on data points from each patient, their risk for retinopathy progression and visual loss can be modeled, allowing them to receive timely treatment. Data can guide algorithms to create models for disease and treatment that may pave the way for more personalized care. Currently, there exist numerous challenges that need to be addressed before reliably building and deploying AI algorithms, including issues with data quality, privacy, intellectual property, and informed consent.
个性化糖尿病眼病护理的目标是实时准确预测糖尿病视网膜病变（DR）进展和视力丧失的风险。电子健康记录（EHR）的使用为人工智能（AI）算法提供了一个平台，这些算法可以预测 DR 的进展并纳入临床决策。通过在每位患者的数据点上实施算法，可以对其视网膜病变进展和视力丧失的风险进行建模，从而使他们能够及时得到治疗。数据可以指导算法为疾病和治疗创建模型，从而为更个性化的护理铺平道路。目前，在可靠地构建和部署 AI 算法之前，还需要解决许多挑战，包括数据质量、隐私、知识产权和知情同意等问题。
