Cancer Research Workforce Development in FAIR Artificial Intelligence and Machine Learning

鉴于可用于癌症和其他疾病的临床和分子数据的收集迅速增长， 人工智能（AI）和机器学习（ML）的潜在应用 更好地应用和更具成本效益的临床决策方法是引人注目的。 然而，AI/ML算法应用的成功，特别是在临床领域， 取决于用于训练和验证AI/ML模型的数据的可用性和质量。 因此，一个未满足的需求是发展所需的能力和技能， 为AI/ML应用做好准备的生物医学数据，可以满足FAIR的四个要求： 可查找、可扩展、可互操作和可重用。我们的综合计划的补充 癌症数据科学通过开发FAIR应用程序的短期课程来满足这一需求 将在三个地点分发：1）通过 南佛罗里达大学主办我们的癌症生物学博士项目，2）动手 为博士后研究员和其他早期阶段的研究人员在莫菲特癌症研讨会 中心，和3）通过莫菲特YouTube频道公开传播录像讲座。

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.