prikaz prve stranice dokumenta Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
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Scientific paper - Review paper
Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
Frontiers in Cardiovascular Medicine, 8 (2022); 765693. https://doi.org/10.3389/fcvm.2021.765693
Sanchez-Martinez, Sergio; Camara, Oscar; Piella, Gemma; Čikes, Maja; González-Ballester, Miguel Ángel; Miron, Marius; Vellido, Alfredo; Gómez, Emilia; Fraser, Alan G.; Bijnens, Bart

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Sanchez Martinez, S., Camara, O., Piella, G., Čikes, M., González Ballester, M. Á., Miron, M. ... Bijnens, B. (2022). Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging. Frontiers in Cardiovascular Medicine, 8.. doi: 10.3389/fcvm.2021.765693

Sanchez Martinez, Sergio, et al. "Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging." Frontiers in Cardiovascular Medicine, vol. 8, 2022. https://doi.org/10.3389/fcvm.2021.765693

Sanchez Martinez, Sergio, Oscar Camara, Gemma Piella, Maja Čikes, Miguel Ángel González Ballester, Marius Miron, Alfredo Vellido, Emilia Gómez, Alan G. Fraser and Bart Bijnens. "Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging." Frontiers in Cardiovascular Medicine 8 (2022). https://doi.org/10.3389/fcvm.2021.765693

Sanchez Martinez, S., et al. (2022) 'Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging', Frontiers in Cardiovascular Medicine, 8. doi: 10.3389/fcvm.2021.765693

Sanchez Martinez S, Camara O, Piella G, Čikes M, González Ballester MÁ, Miron M, and sur.. Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging. Frontiers in Cardiovascular Medicine [Internet]. 2022 January 04 [cited 2024 April 29];8. doi: 10.3389/fcvm.2021.765693

S. Sanchez Martinez, et al., "Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging", Frontiers in Cardiovascular Medicine, vol. 8, January 2022. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:105:785880. [Accessed: 29 April 2024]

Metadata
Title (english)Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
AuthorSergio Sanchez-Martinez
AuthorOscar Camara
AuthorGemma Piella
AuthorMaja Čikes
AuthorMiguel Ángel González-Ballester
AuthorMarius Miron
AuthorAlfredo Vellido
AuthorEmilia Gómez
AuthorAlan G. Fraser
AuthorBart Bijnens
Author's institutionUniversity of Zagreb
School of Medicine
(Department of Internal Medicine)
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Clinical Medical Sciences
Intensive Care
Abstract (english)
The use of machine learning (ML) approaches to target clinical problems is called to revolutionize clinical decision-making in cardiology. The success of these tools is dependent on the understanding of the intrinsic processes being used during the conventional pathway by which clinicians make decisions. In a parallelism with this pathway, ML can have an impact at four levels: for data acquisition, predominantly by extracting standardized, high-quality information with the smallest possible learning curve; for feature extraction, by discharging healthcare practitioners from performing tedious measurements on raw data; for interpretation, by digesting complex, heterogeneous data in order to augment the understanding of the patient status; and for decision support, by leveraging the previous steps to predict clinical outcomes, response to treatment or to recommend a specific intervention. This paper discusses the state-of-the-art, as well as the current clinical status and challenges associated with the two later tasks of interpretation and decision support, together with the challenges related to the learning process, the auditability/traceability, the system infrastructure and the integration within clinical processes in cardiovascular imaging.
Keywords (english)
Languageenglish
Publication typeScientific paper - Review paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titleFrontiers in Cardiovascular Medicine
Numberingvol. 8, 765693
e-ISSN2297-055X
DOIhttps://doi.org/10.3389/fcvm.2021.765693
URN:NBNurn:nbn:hr:105:785880
Publication2022-01-04
Document URLhttps://www.frontiersin.org/articles/10.3389/fcvm.2021.765693/full
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2022-06-30 07:41:44