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Artificial Intelligence in Health AI in the battle against COVID-19

public health management. This review endeavors to careful consideration, particularly in the context of public
delineate the multifaceted applications of AI during the health and the management of personal medical data.
COVID-19 crisis, encompassing disease surveillance,
diagnostic methodologies, therapeutic development, and 2.2. Technological constraints
the optimization of patient care protocols. A particular The technological constraints that define the scope of this
emphasis is placed on the pivotal role of AI in enhancing review are equally significant. While AI holds significant
the efficacy of diagnostic algorithms, which have been potential to enhance pandemic response strategies, its
instrumental in the identification and management of effectiveness depends on the availability of high-quality
COVID-19 cases. Furthermore, the review will scrutinize data, the robustness of algorithms, and the strength of the
the ethical dimensions and data privacy considerations that underlying infrastructure that implements the solutions. 17
are intrinsically linked to the utilization of AI technologies
in the milieu of public health emergencies. 3. Organization of the paper
The significance of AI in the healthcare domain This review is structured to facilitate a comprehensive
during the COVID-19 pandemic has been extensively understanding of the multifarious applications of AI in
documented, with particular regard to its future potential the context of the COVID-19 pandemic. The sections are
and current applications. Moreover, the motivations and systematically organized to provide a logical progression
6,14
imperatives for leveraging AI and big data in response to from historical precedents to future predictions,
the COVID-19 crisis have been thoroughly explored in encompassing the entire spectrum of AI’s contributions to
the literature. An early review has also highlighted the pandemic management.
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contributions and current constraints of AI in combating Section 4 delineates the rigorous approach employed in
COVID-19. This review builds on the foundational work gathering existing literature. It details the strategies used in
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of previous studies but extends beyond them by offering the literature search, the inclusion and exclusion criteria,
a more comprehensive, ethically informed, and future- and the methods of analysis adopted to synthesize the
oriented analysis of AI in the context of the COVID-19 information.
pandemic.
Section 5 explores the historical development of AI in
Notwithstanding the extensive scope of this review, healthcare, with particular emphasis on its role in disease
it is imperative to acknowledge the inherent limitations detection and diagnosis, vaccine development, treatment
that circumscribe its breadth. The dynamic and rapidly strategies, and epidemiology modeling. This section lays
evolving landscape of AI technology, coupled with the the groundwork for understanding AI’s application in the
continuous emergence of novel research, inherently limits COVID-19 pandemic.
the capacity to encapsulate all current initiatives within the
confines of this paper. In light of the voluminous literature Section 6 explores the technical aspects of AI in
pertaining to AI and COVID-19, the focus will be primarily detecting and diagnosing COVID-19. It is further broken
directed towards peer-reviewed articles and seminal case down to highlight the specific contributions of imaging
studies, excluding non-peer-reviewed “grey literature” techniques, natural language processing (NLP), and
and unpublished research work. In addition, the time wearable technologies.
constraints inherent to the writing process may prevent the Section 7 examines AI’s critical role in drug discovery,
inclusion of the most recent developments in the field. patient management, and the evolving realm of
In recognition of these limitations, this review does telemedicine. It underscores AI’s transformative impact on
not claim to be exhaustive; rather, it seeks to furnish improving patient care and optimizing healthcare services.
a comprehensive and representative overview of the Section 8 investigates AI’s predictive capabilities in
current state of AI applications within the context of the epidemiological modeling, resource distribution, and
COVID-19 pandemic, thereby providing a foundational social media analysis for public sentiment and reaction to
understanding of the subject matter and a platform for the pandemic.
future research endeavors.
Section 9 addresses the ethical dilemmas and societal
2.1. Ethical considerations implications of employing AI during a healthcare crisis. It
focuses on crucial issues such as data privacy, algorithmic
The ethical implications of AI deployment in healthcare,
especially during a pandemic, are profound and bias, and unequal access to AI technologies.
multifarious. Issues pertaining to data privacy, informed Section 10 presents a series of case studies that
consent, and the potential for algorithmic bias necessitate demonstrate AI’s practical applications across different

Volume 1 Issue 2 (2024) 3 doi: 10.36922/aih.2401