| Autor: |
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 |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Data in Brief, Vol 32, Iss , Pp 106153- (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2352-3409 |
| DOI: |
10.1016/j.dib.2020.106153 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
