TY - JOUR
T1 - Machine Learning in Cardiology
T2 - A Potential Real-World Solution in Low- and Middle-Income Countries
AU - Alabdaljabar, Mohamad S.
AU - Hasan, Babar
AU - Noseworthy, Peter A.
AU - Maalouf, Joseph F.
AU - Ammash, Naser M.
AU - Hashmi, Shahrukh K.
N1 - Publisher Copyright:
© 2023 Alabdaljabar et al.
PY - 2023
Y1 - 2023
N2 - Artificial intelligence (AI) and machine learning (ML) is a promising field of cardiovascular medicine. Many AI tools have been shown to be efficacious with a high level of accuracy. Yet, their use in real life is not well established. In the era of health technology and data science, it is crucial to consider how these tools could improve healthcare delivery. This is particularly important in countries with limited resources, such as low- and middle-income countries (LMICs). LMICs have many barriers in the care continuum of cardiovascular diseases (CVD), and big portion of these barriers come from scarcity of resources, mainly financial and human power constraints. AI/ML could potentially improve healthcare delivery if appropriately applied in these countries. Expectedly, the current literature lacks original articles about AI/ML originating from these countries. It is important to start early with a stepwise approach to understand the obstacles these countries face in order to develop AI/ML-based solutions. This could be detrimental to many patients’ lives, in addition to other expected advantages in other sectors, including the economy sector. In this report, we aim to review what is known about AI/ML in cardiovascular medicine, and to discuss how it could benefit LMICs.
AB - Artificial intelligence (AI) and machine learning (ML) is a promising field of cardiovascular medicine. Many AI tools have been shown to be efficacious with a high level of accuracy. Yet, their use in real life is not well established. In the era of health technology and data science, it is crucial to consider how these tools could improve healthcare delivery. This is particularly important in countries with limited resources, such as low- and middle-income countries (LMICs). LMICs have many barriers in the care continuum of cardiovascular diseases (CVD), and big portion of these barriers come from scarcity of resources, mainly financial and human power constraints. AI/ML could potentially improve healthcare delivery if appropriately applied in these countries. Expectedly, the current literature lacks original articles about AI/ML originating from these countries. It is important to start early with a stepwise approach to understand the obstacles these countries face in order to develop AI/ML-based solutions. This could be detrimental to many patients’ lives, in addition to other expected advantages in other sectors, including the economy sector. In this report, we aim to review what is known about AI/ML in cardiovascular medicine, and to discuss how it could benefit LMICs.
KW - Artificial intelligence
KW - Cardiology
KW - Countries
KW - Income
KW - Low
KW - Machine learning
KW - Middle
UR - http://www.scopus.com/inward/record.url?scp=85148716918&partnerID=8YFLogxK
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U2 - 10.2147/JMDH.S383810
DO - 10.2147/JMDH.S383810
M3 - Review article
AN - SCOPUS:85148716918
SN - 1178-2390
VL - 16
SP - 285
EP - 295
JO - Journal of Multidisciplinary Healthcare
JF - Journal of Multidisciplinary Healthcare
ER -