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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F23%3A00131767" target="_blank" >RIV/00216224:14610/23:00131767 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1871678423000493" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1871678423000493</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.nbt.2023.09.006" target="_blank" >10.1016/j.nbt.2023.09.006</a>

Result language

angličtina

Original language name

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

Original language description

AI development in biotechnology relies on high-quality data to train and validate algorithms. The FAIR principles (Findable, Accessible, Interoperable, and Reusable) and regulatory frameworks such as the In Vitro Diagnostic Regulation (IVDR) and the Medical Device Regulation (MDR) specify requirements on specimen and data provenance to ensure the quality and traceability of data used in AI development. In this paper, a framework is presented for recording and publishing provenance information to meet these requirements. The framework is based on the use of standardized models and protocols, such as the W3C PROV model and the ISO 23494 series, to capture and record provenance information at various stages of the data generation and analysis process. The framework and use case illustrate the role of provenance information in supporting the development of high-quality AI algorithms in biotechnology. Finally, the principles of the framework are illustrated in a simple computational pathology use case, showing how specimen and data provenance can be used in the development and documentation of an AI algorithm. The use case demonstrates the importance of managing and integrating distributed provenance information and highlights the complex task of considering factors such as semantic interoperability, confidentiality, and the verification of authenticity and integrity.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

NEW BIOTECHNOLOGY

ISSN

1871-6784

e-ISSN

—

Volume of the periodical

78

Issue of the periodical within the volume

DEC

Country of publishing house

DE - GERMANY

Number of pages

7

Pages from-to

22-28

UT code for WoS article

001084774500001

EID of the result in the Scopus database

2-s2.0-85172171953