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TickPhone App: A Smartphone Application for Rapid Tick Identification Using Deep Learning
| Content Provider | MDPI |
|---|---|
| Author | Xu, Zhiheng Ding, Xiong Yin, Kun Li, Ziyue Smyth, Joan Sims, Maureen McGinnis, Holly Liu, Changchun |
| Copyright Year | 2021 |
| Description | Tick species are considered the second leading vector of human diseases. Different ticks can transmit a variety of pathogens that cause various tick-borne diseases (TBD), such as Lyme disease. Currently, it remains a challenge to diagnose Lyme disease because of its non-specific symptoms. Rapid and accurate identification of tick species plays an important role in predicting potential disease risk for tick-bitten patients, and ensuring timely and effective treatment. Here, we developed, optimized, and tested a smartphone-based deep learning algorithm (termed “TickPhone app”) for tick identification. The deep learning model was trained by more than 2000 tick images and optimized by different parameters, including normal sizes of images, deep learning architectures, image styles, and training–testing dataset distributions. The optimized deep learning model achieved a training accuracy of ~90% and a validation accuracy of ~85%. The TickPhone app was used to identify 31 independent tick species and achieved an accuracy of 95.69%. Such a simple and easy-to-use TickPhone app showed great potential to estimate epidemiology and risk of tick-borne disease, help health care providers better predict potential disease risk for tick-bitten patients, and ultimately enable timely and effective medical treatment for patients. |
| Starting Page | 7355 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app11167355 |
| Journal | Applied Sciences |
| Issue Number | 16 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-08-10 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Medical Informatics Tick Identification Smartphone Application Deep Learning Lyme Disease |
| Content Type | Text |
| Resource Type | Article |
