Chinanews.com, Guangzhou, December 12 (Cai Minjie, Tai Mengyun) Artificial intelligence is a hot spot in the fields of medicine, science and technology.
"Artificial intelligence technology is connected to medical diagnosis and treatment, and ophthalmology is a specialty centered on imaging diagnosis." Lin Haotian, deputy director of the Zhongshan Eye Center of Sun Yat-sen University, said on the 12th at the 2020 Smart Medical Academic Conference that ophthalmology has a number of medical imaging And the advantages of quality, these advantages are the breakthrough of the intersection of medicine and artificial intelligence.
The above conference was initiated and hosted by the Chinese Society of Artificial Intelligence, and jointly hosted by Beijing University of Posts and Telecommunications and Sun Yat-sen University Zhongshan Ophthalmology Center.
This conference invited experts and scholars from the field of artificial intelligence, medical research institutes, and university medical technology companies to discuss and discuss the development of basic theories, cutting-edge technologies and key technologies of smart medical care, in order to promote exchanges at home and abroad and accelerate artificial intelligence technology Application in the field of smart medicine.
Lin Haotian, deputy director of the Zhongshan Eye Center of Sun Yat-Sen University, introduced the "development and application of artificial intelligence diagnosis and treatment technology in ophthalmology".
Photo courtesy of Zhongshan Eye Center, Sun Yat-sen University
Zhang Qin, member of the Standing Committee of the National Committee of the Chinese People's Political Consultative Conference, member of the International Academy of Nuclear Energy, and member of the Chinese Society of Artificial Intelligence, introduced the "application of dynamic uncertain causality diagrams in general clinical diagnosis" at the conference.
Zhang Qin’s original Dynamic Uncertain Causality Diagram (DUCG) is an artificial intelligence theory based on the causal knowledge of domain experts.
The theory was first applied to online diagnosis of industrial system faults such as nuclear power plants, and later modified to be used for general clinical assistant diagnosis.
"The general clinical auxiliary diagnosis tool, combined with the above dynamic uncertain causality diagram reasoning algorithm, can diagnose the disease by inputting the patient's condition information, and can dynamically generate individual patients to optimize the clinical diagnosis path to accurately obtain disease information and reduce missed detection Misdiagnosis and misdiagnosis.” Zhang Qin said that the above dynamic uncertain causality diagram is currently being applied in practice in Jiaozhou, Shandong and Zhongxian, Chongqing, and the diagnosis accuracy rate is over 95%.
Lin Haotian made an introduction with the topic of "Development and Application of Ophthalmology Artificial Intelligence Diagnosis and Treatment Technology".
He said that ophthalmology has the advantages of quantity and quality in medical imaging, and it is a breakthrough in the intersection of medicine and artificial intelligence.
At present, Lin Haotian and his team have proposed the "intelligent ophthalmologist" system, which can realize functions such as prediction of myopia development and intelligent assessment of visual function of infants and young children.
During the epidemic this year, he took the lead in implementing the application model of artificial intelligence and Internet hospitals in epidemic prevention and control.
Taking the research and application of artificial intelligence diagnosis and treatment technology in ophthalmology as a breakthrough point, it will help promote medical artificial intelligence technology to serve the society.
In addition, Sun Fuchun, vice chairman of the Chinese Society of Artificial Intelligence and member of the National Key R&D Program Robotics Expert Group, introduced the "Research and Development of Intelligent Medical Robots" at the meeting, analyzing the difficulties faced by the development of medical robots from multiple levels, and proposed based on How deep reinforcement learning-led behavioral intelligence can solve the problems of ethical safety and environmental adaptability in the application of medical robots; Meng Xiangfei, assistant director of the National Supercomputing Center Tianjin, introduced the software and data resources required for integrated smart medical research and development. (Finish)