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Introduction: There is an overwhelming amount of journal articles for modern researchers to parse through. For instance, there have already been 168,168 cancer-related papers archived on PubMed this year. In order to keep up with this substantial amount of literature, there are emerging interests in applying artificial intelligence (AI) to facilitate paper reading and drafting of new scientific ideas. Here, we extend the application of the state-of-the-art automatic research assistants to the cancer field. Using training datasets composed of over 5,000 cancer-related journal papers abstracts, we evaluated AI-based background knowledge extraction and abstract writing. The best AI performance is rated to be on par with human writers through a survey to university cancer researchers. This automatic research assistant tool can potentially speed up scientific discovery and production by helping researchers to efficiently read existing papers, create new ideas and write up new discoveries.