Cargando…

Big data, artificial intelligence, and structured reporting

The past few years have seen a considerable rise in interest towards artificial intelligence and machine learning applications in radiology. However, in order for such systems to perform adequately, large amounts of training data are required. These data should ideally be standardised and of adequat...

Descripción completa

Detalles Bibliográficos
Autores principales: Pinto dos Santos, Daniel, Baeßler, Bettina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279752/
https://www.ncbi.nlm.nih.gov/pubmed/30515717
http://dx.doi.org/10.1186/s41747-018-0071-4
_version_ 1783378530247114752
author Pinto dos Santos, Daniel
Baeßler, Bettina
author_facet Pinto dos Santos, Daniel
Baeßler, Bettina
author_sort Pinto dos Santos, Daniel
collection PubMed
description The past few years have seen a considerable rise in interest towards artificial intelligence and machine learning applications in radiology. However, in order for such systems to perform adequately, large amounts of training data are required. These data should ideally be standardised and of adequate quality to allow for further usage in training of artificial intelligence algorithms. Unfortunately, in many current clinical and radiological information technology ecosystems, access to relevant pieces of information is difficult. This is mostly because a significant portion of information is handled as a collection of narrative texts and interoperability is still lacking. This review aims at giving a brief overview on how structured reporting can help to facilitate research in artificial intelligence and the context of big data.
format Online
Article
Text
id pubmed-6279752
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-62797522018-12-26 Big data, artificial intelligence, and structured reporting Pinto dos Santos, Daniel Baeßler, Bettina Eur Radiol Exp Narrative Review The past few years have seen a considerable rise in interest towards artificial intelligence and machine learning applications in radiology. However, in order for such systems to perform adequately, large amounts of training data are required. These data should ideally be standardised and of adequate quality to allow for further usage in training of artificial intelligence algorithms. Unfortunately, in many current clinical and radiological information technology ecosystems, access to relevant pieces of information is difficult. This is mostly because a significant portion of information is handled as a collection of narrative texts and interoperability is still lacking. This review aims at giving a brief overview on how structured reporting can help to facilitate research in artificial intelligence and the context of big data. Springer International Publishing 2018-12-05 /pmc/articles/PMC6279752/ /pubmed/30515717 http://dx.doi.org/10.1186/s41747-018-0071-4 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Narrative Review
Pinto dos Santos, Daniel
Baeßler, Bettina
Big data, artificial intelligence, and structured reporting
title Big data, artificial intelligence, and structured reporting
title_full Big data, artificial intelligence, and structured reporting
title_fullStr Big data, artificial intelligence, and structured reporting
title_full_unstemmed Big data, artificial intelligence, and structured reporting
title_short Big data, artificial intelligence, and structured reporting
title_sort big data, artificial intelligence, and structured reporting
topic Narrative Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279752/
https://www.ncbi.nlm.nih.gov/pubmed/30515717
http://dx.doi.org/10.1186/s41747-018-0071-4
work_keys_str_mv AT pintodossantosdaniel bigdataartificialintelligenceandstructuredreporting
AT baeßlerbettina bigdataartificialintelligenceandstructuredreporting