Shi Dan, Tang Chunlei, Blackley Suzanne V, Wang Liqin, Yang Jiahong, He Yanming, Bennett Samuel I, Xiong Yun, Shi Xiao, Zhou Li, Bates David W
Department of Geriatrics, Yueyang Hospital of Integrated Traditional Chinese Medicine and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA 02115, USA.
Data Brief. 2020 Aug 8;32:106153. doi: 10.1016/j.dib.2020.106153. eCollection 2020 Oct.
Hospitalized geriatric patients are a highly heterogeneous group often with variable diseases and conditions. Physicians, and geriatricians especially, are devoted to seeking non-invasive testing tools to support a timely, accurate diagnosis. Chinese tongue diagnosis, mainly based on the color and texture of the tongue, offers a unique solution. To develop a non-invasive assessment tool using machine learning in supporting a timely, accurate diagnosis in the elderly, we created an annotated dataset of 15% of 688 (=100) tongue images collected from hospitalized geriatric patients in a tertiary hospital in Shanghai, China. Images were captured via a light-field camera using CIELAB color space (to simulate human visual perception) and then were manually labeled by a panel of subject matter experts after chart reviewing patients' clinical information documented in the hospital's information system. We expect that the dataset can assist in implementing a systematic means of conducting Chinese tongue diagnosis, predicting geriatric syndromes using tongue appearance, and even developing an mHealth application to provide individualized health suggestions for the elderly.
住院老年患者是一个高度异质的群体，往往患有多种不同的疾病和状况。医生，尤其是老年病医生，致力于寻找非侵入性检测工具以支持及时、准确的诊断。中医舌诊主要基于舌头的颜色和质地，提供了一种独特的解决方案。为了开发一种使用机器学习的非侵入性评估工具，以支持对老年人进行及时、准确的诊断，我们创建了一个注释数据集，该数据集包含从中国上海一家三级医院的住院老年患者收集的688张舌图像中的15%（即100张）。图像通过使用CIELAB颜色空间的光场相机拍摄（以模拟人类视觉感知），然后在查阅医院信息系统中记录的患者临床信息图表后，由一组主题专家进行手动标注。我们期望该数据集能够协助实施系统的中医舌诊方法，利用舌象预测老年综合征，甚至开发一款移动健康应用程序，为老年人提供个性化的健康建议。
