دورية أكاديمية

Artificial intelligence and machine learning in hemostasis and thrombosis

التفاصيل البيبلوغرافية
العنوان: Artificial intelligence and machine learning in hemostasis and thrombosis
المؤلفون: Paolo Gresele
المصدر: Bleeding, Thrombosis and Vascular Biology, Vol 2, Iss 4 (2024)
بيانات النشر: PAGEPress Publications, 2024.
سنة النشر: 2024
المجموعة: LCC:Diseases of the circulatory (Cardiovascular) system
مصطلحات موضوعية: Artificial intelligence, machine learning, hemostasis and thrombosis, Diseases of the circulatory (Cardiovascular) system, RC666-701
الوصف: Artificial intelligence (AI) is rapidly becoming more important in our daily lives, and it’s beginning to be used in life sciences and in healthcare. AI and machine learning (ML) models are just starting to be applied in the field of hemostasis and thrombosis, but there are already many examples of how they can be useful in basic research/pathophysiology, laboratory diagnostics, and clinical settings. This review wants to shortly explain how AI works, what have been its uses in hemostasis and thrombosis so far and what are possible future developments. Besides the great potential advantages of a correct application of AI to the field of hemostasis and thrombosis, possible risks of inaccurate or deliberately mischievous use of it must be carefully considered. A close monitoring of AI employment in healthcare and research will have to be applied over the next years, but it is expected that the appropriate employment of this new revolutionary technology will bring great advances to the medical field, including to the hemostasis and thrombosis area. The current review, addressed to non-experts in the field, aims to go through the applications of AI in the field of hemostasis and thrombosis that have been explored so far and to examine its advantages, drawbacks and future perspectives.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2785-5309
العلاقة: https://btvb.org/btvb/article/view/105Test; https://doaj.org/toc/2785-5309Test
DOI: 10.4081/btvb.2023.105
الوصول الحر: https://doaj.org/article/f107444f28ba49ec9603dcddd1496425Test
رقم الانضمام: edsdoj.f107444f28ba49ec9603dcddd1496425
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:27855309
DOI:10.4081/btvb.2023.105