AIDMAN: An AI-based object detection system for malaria diagnosis from smartphone thin-blood-smear images.

Liu, Ruicun; Liu, Tuoyu; Dan, Tingting; Yang, Shan; Li, Yanbing; Luo, Boyu; Zhuang, Yingtan; Fan, Xinyue; Zhang, Xianchao; Cai, Hongmin; Teng, Yue.

Afiliação

Liu R; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Liu T; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Dan T; School of Computer Science and Engineering, South China University of Technology, Guangzhou 510600, China.
Yang S; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Li Y; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Luo B; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Zhuang Y; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Fan X; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
Zhang X; Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China.
Cai H; Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province, Jiaxing University, Jiaxing 314001, China.
Teng Y; School of Computer Science and Engineering, South China University of Technology, Guangzhou 510600, China.