An annotated dataset of tongue images supporting geriatric disease diagnosis

Dan Shi; Chunlei Tang; Suzanne V Blackley; Liqin Wang; Jiahong Yang; Yanming He; Samuel I Bennett; Yun Xiong; Xiao Shi; Li Zhou; David W Bates

doi:10.1016/j.dib.2020.106153

An annotated dataset of tongue images supporting geriatric disease diagnosis

Data Brief. 2020 Aug 8:32:106153. doi: 10.1016/j.dib.2020.106153. eCollection 2020 Oct.

Authors

Dan Shi¹, Chunlei Tang^{2

3}, Suzanne V Blackley^{2

3}, Liqin Wang², Jiahong Yang⁴, Yanming He⁵, Samuel I Bennett^{2

3}, Yun Xiong⁶, Xiao Shi¹, Li Zhou², David W Bates^{2

3}

Affiliations

¹ Department of Geriatrics, Yueyang Hospital of Integrated Traditional Chinese Medicine and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
² Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA 02115, USA.
³ Clinical and Quality Analysis, Mass General Brigham, Somerville, MA 02145, USA.
⁴ Shanghai Shenkang Hospital Development Center, Shanghai 200041, China.
⁵ Department of Endocrinology, Yueyang Hospital of Integrated Traditional Chinese Medicine and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
⁶ Shanghai Key Laboratory of Data Science, School of Computer science, Fudan University, Shanghai 201203, China.

Abstract

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.

Keywords: Clinical documentation; geriatric diseases; tongue images.