人工智能白内障协同管理的通用平台OA
Universal artificial intelligence platform for collaborative management of cataracts(authorized Chinese translation)
目的:建立和验证一个涉及多级临床场景的白内障协作通用的人工智能(artificial intelligence,AI)管理平台,探索基于AI的医疗转诊模式,以提高协作效率和资源覆盖率.方法:训练和验证的数据集来自中国AI医学联盟,涵盖多级医疗机构和采集模式.使用三步策略对数据集进行标记:1)识别采集模式;2)白内障诊断包括正常晶体眼、白内障眼或白内障术后眼;3)从病因和严重程度检测需转诊的白内障患者.此外,将白内障AI系统与真实世界中的居家自我监测、初级医疗保健机构和专科医院等多级转诊模式相结合.结果:通用AI平台和多级协作模式在三步任务中表现出可靠的诊断性能:1)识别采集模式的受试者操作特征(receiver operating characteristic curve,ROC)曲线下面积(area under the curve,AUC)为99.28％～99.71％);2)白内障诊断对正常晶体眼、白内障或术后眼,在散瞳-裂隙灯模式下的AUC分别为99.82％、99.96％和99.93％,其他采集模式的AUC均＞99％;3)需转诊白内障的检测(在所有测试中AUC＞91％).在真实世界的三级转诊模式中,该系统建议30.3％的人转诊,与传统模式相比,眼科医生与人群服务比率大幅提高了 10.2倍.结论:通用AI平台和多级协作模式显示了准确的白内障诊断性能和有效的白内障转诊服务.建议AI的医疗转诊模式扩展应用到其他常见疾病和资源密集型情景当中.
Objective:To establish and validate a universal artificial intelligence(AI)platform for collaborative management of cataracts involving multilevel clinical scenarios and explored 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,covering multilevel healthcare facilities and capture modes.The datasets were labelled 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 aetiology and severity Moreover,we integrated the cataract AI agent with a real-world multilevel referral pattem involving self-monitoring at home,primary healthcare and specialised hospital services.Results:The universal AI platform and multilevel collaborative pattern showed robust diagnostic performance in three-step tasks:(1)capture mode recognition(area under the curve(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 with the traditional pattern.Conclusions: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.
WU Xiaohang;YU Tongyong;WU Dongxuan;LI Cong;CHEN Yanyi;ZOU Minjie;CHEN Chuan;ZHU Yi;GUO Chong;ZHANG Xiayin;WANG Ruixin;HUANG Yelin;YANG Yahan;XIANG Yifan;CHEN Lijian;LIU Congxin;XIONG Jianhao;GE Zongyuan;WANG Dingding;XU Guihua;DU Shaolin;XIAO Chi;LIU Zhenzhen;WU Jianghao;ZHU Ke;NIE Danyao;XU Fan;LV Jian;CHEN Weirong;LIU Yizhi;LIN Haotian;《眼科学报》出版团队;王厚硕;LAI Weiyi;罗明杰;林浩添;LONG Erping;ZHANG Kai;JIANG Jiewei;LIN Duoru;CHEN Kexin
State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,China||Department of Molecular and Cellular Pharmacology,University of Miami Miller School of Medicine,Miami,Florida,USAState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,China||Department of Molecular and Cellular Pharmacology,University of Miami Miller School of Medicine,Miami,Florida,USAState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaBeijing Tulip Partners Technology Co.,Ltd,Beijing,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaBeijing Tulip Partners Technology Co.,Ltd,Beijing,ChinaBeijing Tulip Partners Technology Co.,Ltd,Beijing,ChinaBeijing Tulip Partners Technology Co.,Ltd,Beijing,ChinaDepartment of Electrical and Computer Systems Engineering,Faculty of Engineering,Monash University,Melbourne,Victoria,AustraliaHuizhou Municipal Central Hospital,Huizhou,ChinaHuizhou Municipal Central Hospital,Huizhou,ChinaTung Wah Hospital,Sun Yat-sen University,Dongguan,ChinaDongguan Guangming Ophthalmic Hospital,Dongguan,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaDongguan Guangming Ophthalmic Hospital,Dongguan,ChinaKaifeng Eye Hospital,Kaifeng,ChinaShenzhen Eye Hospital,Shenzhen Key Laboratory of Ophthalmology,Shenzhen University School of Medicine,Shenzhen,ChinaDepartment of Ophthalmology,People's Hospital of Guangxi Zhuang Autonomous Region,Nanning,ChinaDepartment of Ophthalmology,People's Hospital of Guangxi Zhuang Autonomous Region,Nanning,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,China西安交通大学第一附属医院State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,China中山大学中山眼科中心,眼病防治全国重点实验室,广东省眼科视觉科学重点实验室State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaSchool of Computer Science and Technology,Xidian University,Xi'an,ChinaSchool of Computer Science and Technology,Xidian University,Xi'an,ChinaState Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,ChinaZhongshan School of Medicine,Sun Yat-sen University,Guangzhou,China
《眼科学报》 2023 (10)
晶状体再生修复过程中TGF-β通过EGFR通路调控EMT的分子机制
665-675,11
国家重点研发计划(2018YFC0116500),国家自然科学基金重点研究计划(91846109),国家自然科学优秀青年基金(81822010),国家自然科学基金(81770967,81873675,81800810),广东省科技计划项目(2019B030316012,2018B010109008,2017B030314025),广东科技创新领军人才计划(2017TX04R031),广东省自然科学基金(2018A030310104).
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