The role of machine learning in healthcare responses to pandemics: maximizing benefits and filling gaps

Ahmad Z. Al Meslamani; Anan S. Jarab; Mohammad A. Ghattas

doi:10.1080/13696998.2023.2224018

The role of machine learning in healthcare responses to pandemics: maximizing benefits and filling gaps

Al Ain University of Science and Technology

Jordan University of Science and Technology

Research output: Contribution to journal › Editorial

8 Scopus citations

Original language	English
Pages (from-to)	777-780
Number of pages	4
Journal	Journal of Medical Economics
Volume	26
Issue number	1
DOIs	https://doi.org/10.1080/13696998.2023.2224018
State	Published - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1080/13696998.2023.2224018

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title = "The role of machine learning in healthcare responses to pandemics: maximizing benefits and filling gaps",

author = "\{Al Meslamani\}, \{Ahmad Z.\} and Jarab, \{Anan S.\} and Ghattas, \{Mohammad A.\}",

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TY - JOUR

T1 - The role of machine learning in healthcare responses to pandemics

T2 - maximizing benefits and filling gaps

AU - Al Meslamani, Ahmad Z.

AU - Jarab, Anan S.

AU - Ghattas, Mohammad A.

PY - 2023

Y1 - 2023

UR - https://www.scopus.com/pages/publications/85163206257

U2 - 10.1080/13696998.2023.2224018

DO - 10.1080/13696998.2023.2224018

M3 - Editorial

C2 - 37293941

AN - SCOPUS:85163206257

SN - 1369-6998

VL - 26

SP - 777

EP - 780

JO - Journal of Medical Economics

JF - Journal of Medical Economics

IS - 1

ER -

The role of machine learning in healthcare responses to pandemics: maximizing benefits and filling gaps

UN SDGs

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