lancet-header

Preprints with The Lancet is part of SSRN´s First Look, a place where journals identify content of interest prior to publication. Authors have opted in at submission to The Lancet family of journals to post their preprints on Preprints with The Lancet. The usual SSRN checks and a Lancet-specific check for appropriateness and transparency have been applied. Preprints available here are not Lancet publications or necessarily under review with a Lancet journal. These preprints are early stage research papers that have not been peer-reviewed. The findings should not be used for clinical or public health decision making and should not be presented to a lay audience without highlighting that they are preliminary and have not been peer-reviewed. For more information on this collaboration, see the comments published in The Lancet about the trial period, and our decision to make this a permanent offering, or visit The Lancet´s FAQ page, and for any feedback please contact preprints@lancet.com.

A Universal Artificial Intelligence Platform for Collaborative Management of Cataracts

35 Pages Posted: 14 Mar 2019

See all articles by Xiaohang Wu

Xiaohang Wu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Zhenzhen Liu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Weiyi Lai

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Erping Long

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Kai Zhang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Jiewei Jiang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Duoru Lin

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Kexin Chen

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Tongyong Yu

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Dongxuan Wu

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Cong Li

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Yanyi Chen

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Minjie Zou

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

Chuan Chen

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Yi Zhu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Chong Guo

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Xiayin Zhang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Ruixin Wang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Yahan Yang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Yifan Xiang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Yuzhong Chen

Beijing Tulip Partners Technology Co., Ltd.

Jianhao Xiong

Beijing Tulip Partners Technology Co., Ltd.

Dingding Wang

Huizhou Municipal Central Hospital

Guihua Xu

Huizhou Municipal Central Hospital

Shaolin Du

Sun Yat-sen University (SYSU)

Chi Xiao

Dongguan Guangming Ophthalmic Hospital

Jianghao Wu

Dongguan Guangming Ophthalmic Hospital

Ke Zhu

Kaifeng Eye Hospital

Danyao Nie

Shenzhen University - School of Medicine

Fan Xu

People’s Hospital of Guangxi Zhuang Autonomous Region

Jian Lv

People’s Hospital of Guangxi Zhuang Autonomous Region

Weirong Chen

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

Yizhi Liu

Sun Yat-sen University (SYSU) - State Key Laboratory of Ophthalmology

Haotian Lin

Sun Yat-sen University (SYSU) - State Key Laboratory of Ophthalmology

More...

Abstract

Background:  The current healthcare system is unsatisfactory for the management of high-incidence diseases, such as cataract, due to inadequate medical resources and limited accessibility. Artificial intelligence (AI) holds great promise but remains to be improved to integrate it into primary healthcare services for increased patient coverage. The goals of this study were to establish and validate a universal AI platform for the collaborative management of cataracts involving multilevel clinical scenarios and to explore an AI-based medical referral pattern to improve collaborative efficiency and resource coverage.  

Methods:  The training and validation datasets were derived from the Chinese Medical Alliance for Artificial Intelligence (CMAAI), covering multilevel healthcare facilities and capture modes. The datasets were labeled using a three-step strategy: (1) capture mode recognition; (2) cataract diagnosis as a normal lens, cataract or a postoperative eye; and (3) detection of referable cataracts with respect to etiology and severity. Moreover, we integrated the cataract AI agent with a real-world multilevel referral pattern involving self-monitoring at home, primary healthcare, and specialized hospital services.  

Findings:  The universal AI platform and multilevel collaborative pattern showed robust diagnostic performance in three-step tasks: (1) capture mode recognition (AUC 99.28%-99.71%), (2) cataract diagnosis (normal lens, cataract or postoperative eye with AUCs of 99.82%, 99.96%, and 99.93% for mydriatic-slit lamp mode and AUCs >99% for other capture modes), and (3) detection of referable cataracts (AUCs>91% in all tests). In the real-world tertiary referral pattern, the agent suggested 30.3% of people be "referred", substantially increasing the ophthalmologist-to-population service ratio by 10.2-fold compared to the traditional pattern.  

Interpretation  The universal AI platform and multilevel collaborative pattern showed robust diagnostic performance and effective service for cataracts. The context of our AI-based medical referral pattern will be extended to other common disease conditions and resource-intensive situations to provide cost-effective health care for an increasing number of patients.  

Trial Registration Number: This study was registered with ClinicalTrials.gov (identifier: NCT03623971).

Funding Statement:  This study was supported by the National Key Research and Development Program (2018YFC0116500), the Key Research Plan for the National Natural Science Foundation of China in Cultivation Project (91546101), the Science Foundation of China for Excellent Young Scientists (8182200130), the Guangdong Provincial Natural Science Foundation for Distinguished Young Scholars of China (2014A030306030), the Guangdong Province Universities and Colleges Youth Pearl River Scholar Funded Scheme (Haotian Lin), the National Natural Science Foundation of China (81800810), the Natural Science Foundation of Guangdong Province (2018A030310104), the Science and Technology Planning Projects of Guangdong Province (2017B030314025), the Clinical Research and Translational Medical Center of Pediatric Cataract in Guangzhou City (201505032017516), the Outstanding Young Teacher Cultivation Projects in Guangdong Province (YQ2015006), the Fundamental Research Funds for the Central Universities (16ykjc28)

Declaration of Interests: The authors declare that they have no competing financial interests to disclose.

Ethics Approval Statement: Ethical review of the study was performed by the Zhongshan Ophthalmic Center Ethics Review Committee.

Keywords: artificial intelligence platform; cataracts diagnosis; medical resource coverage

Suggested Citation

Wu, Xiaohang and Liu, Zhenzhen and Lai, Weiyi and Long, Erping and Zhang, Kai and Jiang, Jiewei and Lin, Duoru and Chen, Kexin and Yu, Tongyong and Wu, Dongxuan and Li, Cong and Chen, Yanyi and Zou, Minjie and Chen, Chuan and Zhu, Yi and Guo, Chong and Zhang, Xiayin and Wang, Ruixin and Yang, Yahan and Xiang, Yifan and Chen, Yuzhong and Xiong, Jianhao and Wang, Dingding and Xu, Guihua and Du, Shaolin and Xiao, Chi and Wu, Jianghao and Zhu, Ke and Nie, Danyao and Xu, Fan and Lv, Jian and Chen, Weirong and Liu, Yizhi and Lin, Haotian, A Universal Artificial Intelligence Platform for Collaborative Management of Cataracts (March 13, 2019). Available at SSRN: https://ssrn.com/abstract=3352014 or http://dx.doi.org/10.2139/ssrn.3352014

Xiaohang Wu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Zhenzhen Liu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Weiyi Lai

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Erping Long

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Kai Zhang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Jiewei Jiang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Duoru Lin

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Kexin Chen

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Tongyong Yu

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Dongxuan Wu

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Cong Li

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Yanyi Chen

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Minjie Zou

Sun Yat-sen University (SYSU) - Zhongshan School of Medicine

No. 74 Zhongshan Rd. 2
Guangzhou, 510080
China

Chuan Chen

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Yi Zhu

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Chong Guo

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Xiayin Zhang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Ruixin Wang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Yahan Yang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Yifan Xiang

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Yuzhong Chen

Beijing Tulip Partners Technology Co., Ltd.

Beijing, 100044
China

Jianhao Xiong

Beijing Tulip Partners Technology Co., Ltd.

Beijing, 100044
China

Dingding Wang

Huizhou Municipal Central Hospital

Huizhou, 516002
China

Guihua Xu

Huizhou Municipal Central Hospital

Huizhou, 516002
China

Shaolin Du

Sun Yat-sen University (SYSU)

135, Xingang Xi Road
Haizhu District
Guangzhou, Guangdong 510275
China

Chi Xiao

Dongguan Guangming Ophthalmic Hospital

Dongguan, 523290
China

Jianghao Wu

Dongguan Guangming Ophthalmic Hospital

Dongguan, 523290
China

Ke Zhu

Kaifeng Eye Hospital

Kaifeng, 475000
China

Danyao Nie

Shenzhen University - School of Medicine

China

Fan Xu

People’s Hospital of Guangxi Zhuang Autonomous Region

Nanning, 530021
China

Jian Lv

People’s Hospital of Guangxi Zhuang Autonomous Region

Nanning, 530021
China

Weirong Chen

Sun Yat-sen University (SYSU) - Zhongshan Ophthalmic Center

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Yizhi Liu

Sun Yat-sen University (SYSU) - State Key Laboratory of Ophthalmology

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Haotian Lin (Contact Author)

Sun Yat-sen University (SYSU) - State Key Laboratory of Ophthalmology ( email )

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

Click here to go to TheLancet.com

Paper statistics

Downloads
77
Abstract Views
864
PlumX Metrics