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Cancer Informatics in 2019: Deep Learning Takes Center Stage
21 August 2020 (online)
Objective: To summarize significant research contributions on cancer informatics published in 2019.
Methods: An extensive search using PubMed/Medline and manual review was conducted to identify the scientific contributions published in 2019 that address topics in cancer informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of two best papers was conducted by the editorial committee of the Yearbook.
Results: The two selected best papers demonstrate the clinical utility of deep learning in two important cancer domains: radiology and pathology.
Conclusion: Cancer informatics is a broad and vigorous subfield of biomedical informatics. Applications of new and emerging computational technologies are especially notable in 2019.
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