Recent digital world, dominated by data, has opened, healthcare-related data is also explosively increasing. If such healthcare big data is properly utilized, it could be possible to reduce medical costs, to apply all aspects of predicting, diagnosing and treating diseases. Especially in musculoskeletal health, various data such as imaging and laboratory test results are important indicators for medical judgement. In addition, it will be a great contribution to musculoskeletal health if medical big data and machine learning are combined. Therefore, we organize this symposium with three big data and machine learning experts. First, Professor Daniel Prieto-Alhambra from Oxford University will give a lecture of ‘Emerging Trends of Big Data Analysis on Bone Health’. Professor Daniel Prieto-Alhambra received formal training in Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. He has extensive expertise in the design, curation, and analysis of electronic medical records, claims, registry and other real world data from all over the world.
Next, Professor Namgi Hong from Yonsei University, who has experience in conducting a lot of research with big data available in Korea, will give a lecture of ‘Spectrum and Utilization of Medical Big Data for Bone Research in Korea’. Professor Namgi Hong has successfully conducted clinical research for prediction and prevention of metabolic diseases and sarcopenia using medical big data, so he will give useful lectures on research and patient treatment using Korean medical big data.
Lastly, Professor Yul Hwangbo from National Cancer Center will give a lecture of ‘Clinical Application of Machine-Learning in Musculoskeletal Disease’. Professore Yul Hwangbo is a team manager of Healthcare AI (artificial intelligence) Team at National Cancer Center, one of the future leader in Korea. Therefore, he could suggest utilization of medical data and machine learning to apply these things to the actual patient care.