LAUSR

Medical big data science research such as radiomics has soared in recent years and found many potential applications in medical physics. In contrast to the tremendous interests in these exciting new directions, comprehensive learning materials and books have been scarce on these topics, especially those that tailor toward the radiation oncology and radiology communities. Despite an abundance of research papers and some review articles, there have not been many comprehensive books devoted to these special audiences. Two first‐ edition books published in 2019 by the Taylor and Francis Group, Radiomics and Radiogenomics (edited by Ruijiang Li, Lei Xing, Sandy Napel, and Daniel L. Rubin) and Big Data in Radiation Oncology (edited by Jun Deng and Lei Xing), have opportunely filled this void, and provided a comprehensive review as well as valuable insights on these key new advances. The chapter authors for the two books are reputable experts on related research areas, including many leading figures such as Robert Gillies, Maryellen Giger, Joseph Deasy, Issam Naqa, Laurence Court, and Charles Mayo. The books belong to an ongoing book series titled “Imaging in Medical Diagnosis and Therapy” that was first initiated over a decade ago by a group of senior leaders in the medical physics community, with each volume to address “a rapidly advancing area of medical imaging or radiation therapy of importance to medical physicists”.