Applications of artificial intelligence, mathematical modeling and simulation in medical biophysics

摘要

Mathematical modeling and simulation have been used for years to solve various problems in medical biophysics, such as computational methods incorporating biomedical knowledge and automate reasoning. Recently, we are witnessing the renaissance of artificial intelligence (AI), accentuated by the rapid advances of internet-based computing technologies, namely, big data analytics and cloud computing [1]. Nobel laureate George Bernard Shaw said: “Progress is impossible without change, and those who cannot change their minds cannot change anything.” [2]. AI brought about sweeping changes in recent years and accounted for a large number of incredible progress in medical biophysics such as cancer therapy, nanotechnology and drug delivery [3]. AI also changed the way people think, and played key roles in decision making and problem solving. Just imagine how a machine having “human” intelligence can help you complete a task. The process is basically done by machine learning, a specific AI algorithm capable of computing large datasets, while recognizing the complexity within the detailed patterns [4]. Using a computing system of artificial neural networks which consist of the input, output and hidden layers, a model built by machine learning can answer complex question. To date, AI takes advantage of the big data cloud advancement because of the huge amount of data acquired for machine training [1]. By using the pay-as-you-go approach, appropriate amount of computing resources such as CPU time, storage and software can be purchased from the service provider to finish the job. This flexible approach makes data transfer, storage and processing flexible as it takes place in a remote cloud, in which software updates can take place quickly.