Provenance of specimen and data - A prerequisite for AI development in computational pathology.

[1]  P. Holub,et al.  Lightweight Distributed Provenance Model for Complex Real–world Environments , 2022, Scientific Data.

[2]  Evert-Ben van Veen,et al.  The Ten Commandments of Ethical Medical AI , 2021, Computer.

[3]  M. Plass,et al.  Digital Pathology: Advantages, Limitations and Emerging Perspectives , 2020, Journal of clinical medicine.

[4]  Keith Russell,et al.  The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments , 2020, Data Sci. J..

[5]  Julio Rubio,et al.  A systematic review of provenance systems , 2018, Knowledge and Information Systems.

[6]  Adeel Anjum,et al.  Trustworthy data: A survey, taxonomy and future trends of secure provenance schemes , 2017, J. Netw. Comput. Appl..

[7]  Petr Holub,et al.  Toward Global Biobank Integration by Implementation of the Minimum Information About BIobank Data Sharing (MIABIS 2.0 Core). , 2016, Biopreservation and biobanking.

[8]  E. Benson,et al.  A new quality management perspective for biodiversity conservation and research: Investigating Biospecimen Reporting for Improved Study Quality (BRISQ) and the Standard PRE-analytical Code (SPREC) using Natural History Museum and culture collections as case studies , 2016 .

[9]  J. Ioannidis,et al.  Reproducibility in Science: Improving the Standard for Basic and Preclinical Research , 2015, Circulation research.

[10]  Vasa Curcin,et al.  Implementing interoperable provenance in biomedical research , 2014, Future Gener. Comput. Syst..

[11]  M. Buck,et al.  The Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity , 2011 .

[12]  Santana de Souza,et al.  Protection , 2020, Encyclopedia of the UN Sustainable Development Goals.

[13]  Kishu Manghani,et al.  Quality assurance: Importance of systems and standard operating procedures , 2011, Perspectives in clinical research.