 A.I. is quite well-advanced now, specifically taking into account this A.I. is from the centralized A.I. development is going to personalize or tailored to the specific service and obligations as is one of the important domains to advance of this A.I. technology to tailored as a related subject that is a major part. Following of this, your second question is that most important part is a promising part should be how we can recognize those pattern recognition by scanning of these medical photos, medical scans, medical images that are many of areas even analyzing the medical data which might be A.I. is better than the human being's abilities. Only from this accuracy and reliability aspect. For getting benefit of this A.I. for health, we need data. But this data is possibly we understand data should be human, especially race-oriented, some of sex-oriented, some of age-oriented, some of country-oriented regionals. So data will be quite widely spread out. So how we can collect all this data, how we can verify all this data, how we can ensure this genitive of this data. All this is a very challenging subject. And all collected data become of this global applications. That is another big challenge. That's the reason why this I.T.U. get together with WHO as UN agencies to address all this data or use of A.I. for health in global sense. It might be misunderstood outside. So we try to develop some A.I. standard or health standard. This is out of our scope. I want to say this is quite early stage. So important part is after collecting of this health data with some applying of this A.I. technologies, we may find some of the pieces of this, some of called snapshots, snapshots of this subject areas. We can continuously recursive of this. And with this collected snapshots, we may use benchmark to apply, to apply specific cases, to apply specific countries. We get this assessment after this benchmarking tools. It will be very helpful for all citizens who need assistance from A.I. for health. After we continue this exercise, we may have a good opportunity, better situations to get this A.I. for health to enhance this health environment. Even this first meeting always very important because this health community, IT community is quite different. They separated. It was separated. Different community, even IT, WHO as different organizations. So we might have some use of different language, maybe use of the same language for different objectives. And also our understanding of this, different other side, like IT community's understanding of health ideas, health community's understanding of IT technologies might be limited. So this first meeting is we can show this our experiences. We can try to set the scene of this how we can start together with the same ground, same language, same frameworks. This is main objective. So this workshop today is a special address on this. So after this first meeting, we will move forward the practical subject, practical issues, how to collect, how to assess, how to find out some of solutions.