Advances in Platelet-Dysfunction Diagnostic Technologies.


Journal

Biomolecules
ISSN: 2218-273X
Titre abrégé: Biomolecules
Pays: Switzerland
ID NLM: 101596414

Informations de publication

Date de publication:
17 Jun 2024
Historique:
received: 30 04 2024
revised: 07 06 2024
accepted: 11 06 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 27 6 2024
Statut: epublish

Résumé

The crucial role of platelets in hemostasis and their broad implications under various physiological conditions underscore the importance of accurate platelet-function testing. Platelets are key to clotting blood and healing wounds. Therefore, accurate diagnosis and management of platelet disorders are vital for patient care. This review outlines the significant advancements in platelet-function testing technologies, focusing on their working principles and the shift from traditional diagnostic methods to more innovative approaches. These improvements have deepened our understanding of platelet-related disorders and ushered in personalized treatment options. Despite challenges such as interpretation of complex data and the costs of new technologies, the potential for artificial-intelligence integration and the creation of wearable monitoring devices offers exciting future possibilities. This review underscores how these technological advances have enhanced the landscape of precision medicine and provided better diagnostic and treatment options for platelet-function disorders.

Identifiants

pubmed: 38927117
pii: biom14060714
doi: 10.3390/biom14060714
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : the IITP and funded by the Ministry of Science and ICT (MSIT)
ID : IITP-2023-RS-2023-00260267
Organisme : the National Research Foundation of Korea (NRF) grant
ID : RS-2023-00213379
Organisme : Korea and Regional Innovation Strategy (RIS)
ID : 2022RIS-005

Auteurs

Inkwon Yoon (I)

Department of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.

Jong Hyeok Han (JH)

Department of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.

Hee-Jae Jeon (HJ)

Department of Smart Health Science and Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.
Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon 24341, Republic of Korea.

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Classifications MeSH