Virtual autopsy: Machine Learning and Artificial Intelligence provide new opportunities for investigating minimal tumor burden and therapy resistance by cancer patients

Authors

  • Shane O’Sullivan University of São Paulo, Faculty of Medicine, Department of Pathology
  • Andreas Holzinger Medical University of Graz, Institute for Medical Informatics/Statistics
  • Dominic Wichmann University Hospital Hamburg Eppendorf, Department of Intensive Care
  • Paulo Hilario Nascimento Saldiva University of São Paulo, Faculty of Medicine, Department of Patholog
  • Mohammed Imran Sajid Wirral University Teaching Hospital, Department of Upper GI Surgery
  • Kurt Zatloukal Medical University of Graz, Institute of Pathology

DOI:

https://doi.org/10.4322/acr.2018.003

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Published

2018-03-13

Issue

Vol. 8 No. 1 (2018)

Section

Letters to the Editor

License

Authors of articles published by Autopsy and Case Report retain the copyright of their work without restrictions, licensing it under the Creative Commons Attribution License - CC-BY, which allows articles to be re-used and re-distributed without restriction, as long as the original work is correctly cited.

How to Cite

O’Sullivan, S., Holzinger, A., Wichmann, D., Saldiva, P. H. N., Sajid, M. I., & Zatloukal, K. (2018). Virtual autopsy: Machine Learning and Artificial Intelligence provide new opportunities for investigating minimal tumor burden and therapy resistance by cancer patients. Autopsy and Case Reports, 8(1), e2018003. https://doi.org/10.4322/acr.2018.003