Cancer Research Workforce Development in FAIR Artificial Intelligence and Machine Learning

鉴于快速增长的临床和分子数据收集可用于癌症和其他

Given the rapidly growing collection of clinical and molecular data available for cancer and other diseases, the potential application of artificial intelligence (AI) and machine learning (ML) approaches applied better and more cost-effective clinical decision making is compelling. However, the success of the application of AI/ML algorithms, especially in the clinical domain, hinges on the availability and quality of data for training and validation of the AI/ML models. Therefore, an unmet need is in the development of competencies and skills needed to make biomedical data ready for AI/ML applications that can meet the four FAIR requirements: Findable, Accessible, Interoperable, and Reusable. This supplement to our Integrated Program in Cancer Data Science addresses this need by developing a short course in FAIR application that will be distributed in three venues: 1) a short-course for Ph.D student offer through the University of South Florida, which host our Cancer Biology PhD Program, 2) hands-on workshops for postdoctoral fellows and other early-staged investigator at the Moffitt Cancer Center, and 3) public dissemination of videotaped lectures via Moffitt YouTube channel.