لخّصلي

Egypt had become a safer place to live and do business, and to achieve Egypt's Vision 2030, the country has begun to adopt artificial intelligence and technology in various sectors.Hence, nurse leaders need to foster positive attitudes towards AI technologies (Ronquillo et al., 2021), and to assist AI"s beneficial deployment in future health care there are clear needs to understand nurse leaders" and developers" current perceptions of AI. This would provide insights into how AI could be developed to best serve health care organizations, clinicians" workflows and patient care. Such insights would be highly valuable for developers of AI, health care organizations and decision makers seeking to develop and implement effective AI-based solutions.Artificial intelligence refers broadly to computing technologies which resemble processes related to human intelligence, as reasoning, adaptation and learning, sensory understanding and interaction (Hassanzadeh, et al., 2018). The developing use cases of artificial intelligence in the sector of healthcare might be shown as technologies collection which enable machines to perceive, understand, act and learn in order to carry out healthcare administrative and clinical functions, in addition to be enrolled in research and for clinical learning activities. For the last time, Artificial intelligence has increased productivity and its extensive widespread into daily life is increasing at a rapid pace (Taei,2020)AI has been divided into many subdisciplines, focusing on very distinct problems (such as vision, problem solving, language comprehension, learning, etc.) (Lai et al., 2020). Artificial intelligence (AI) is also defined as a collection of technologies that uses complex algorithms and software to emulate human cognition in the analysis, interpretation and understanding of complex healthcare data. AI can enhance the ability for nurses to better grasp the day-to-day patterns and needs of their patients. According to Eric Topol, (2019), the promise of AI is to provide a complete, panoramic view of an individual"s health information; to improve decision making; to eliminate errors such as misdiagnosis and unnecessary procedures; to assist with ordering and interpreting appropriate tests; and to recommend treatment.The AIT includes numerous healthcare technologies that can alter nurses' roles and improve patients' care, including robots, algorithms, risk prediction, speech recognition, and clinical decision support (Robert, 2019; Pailaha, 2023).Artificial Intelligence (AI) has been transformative for many public and private industries, and we are currently observing an AI-led revolution in healthcare.Risk factors for adverse maternal health outcomes during pregnancy can include a variety of factors such as age, pre-existing medical conditions, lifestyle factors, and socioeconomic status (Londero et al., 2019; Crear-Perry et al., 2021).Artificial Intelligence Technology (AIT) is a branch of computer science designed to imitating of by human brain by realizing tasks or solving problems also used in nursing care of patient, and automating various processes, including learning and decision-making (Maddox et al., 2019).Nowadays, the healthcare world endorses a fast technological evolution, including emerging artificial intelligence technology (AIT).Also, AI has been used in predicting the onset of pregnancy conditions such as preeclampsia, and gestational diabetes mellitus, and in the management of diseases such as ectopic pregnancy (Abuelezz et al., 2022).Identifying high-risk pregnancies is a critical step in ensuring maternal and fetal health, but it can be a challenging task due to the complexity and variability of the factors involved.Artificial intelligence has many applications in healthcare, including assisting in disease assessment, diagnosis, and solving various clinical problems, reducing lost data, enhancing good nursing communication skills, improving inpatient care management, diminish nurse workload, and improving patient safety (Zhou et al.,2022).As well, Liu et al. (2022),clarified that nursing intervention canadvantage from AI-based medical information processing.Perception toward artificial intelligence is defined as the integration of sensory impressions into information that is psychologically meaningful (Kundaliya et al., 2022).So, nurses have to be immersed in conceptualizing, developing, and implementing AIT.Additionally, Artificial intelligence technologieshave the capability advance nursing performance and make it possible for nurses to give their patients more individualized, evidence - based care through improvingnurses' professional and helping in solving the problems (Abd ElMonem, 2023).In addition to shifting from paper to mostly digital patient records, other tools such as wearable technology, mobile apps, smart beds, and mobile monitoring devices have been added to the nursing toolkit and have been identified as significant recent technological advancements in nursing practice.This lack of knowledge may increase anxiety and arouse conflicting emotions in clinical staff which may affect their perceptions of AI (Abdullah & Fakieh, 2020)Attitudes toward artificial intelligence is defined as a learned association in memory between artificial intelligence and a positive or negative evaluation of artificial intelligence, and attitude strength is equivalent to the strength of this association (Brown, 2022).Various health care professionals, particularly clinicians, reportedly have mixed attitudes towards AI (Abdullah & Fakieh, 2020), and it has been claimed that they understand neither) how AI uses algorithms nor the inner workings of algorithms (RomeroBrufau et al., 2020).The vast majority of these deaths (94%) occurred in low-resource settings, and most could have been prevented (WHO, 2019).In recent years, artificial intelligence (AI) has emerged as a powerful tool in healthcare, offering new ways to analyze and interpret complex medical data.A study by Akazawa and Hashimoto (Akazawa and Hashimoto, 2022) evaluated the accuracy of AI in predicting preterm birth in pregnancy, in a bid to increase preparedness and reduce neonatal deaths.The common predictive values used were electrohysterogram images, the metabolic panels in amniotic fluid or maternal blood, obstetric ultrasound images of the cervix, and biological profiles of mothers.or to the offspring such as prematurity, perinatal asphyxia, congenital anomalies and even cardiovascular abnormalities in adulthood (Majella et al., 2019; Yoon, 2021).These models can help healthcare providers make more accurate and timely decisions; and when it refers to maternal health care in pregnancy, it can ultimately improve maternal and fetal health outcomes.AI offers novel approaches to prediction modeling, diagnosis as well as early detection of pregnancies at risk (Ramakrishnan et al., 2021).regarding an Egyptian society powered by artificial intelligence and robotics, the government has set a general target of 7.7% of Egypt's Gross Domestic Product to be derived from artificial intelligence and robotics by 2030 (Egypt's Artificial Intelligence Future, 2020).Nursing practice has become more standardized than in the past, which requires nurses to make more important decisions.Despite advances in medical science, maternal mortality remains a significant problem in many countries, particularly in developing nations (Olonade et al., 2019; Musarandega et al., 2021).So, it is necessary to adapt the traditional role of nurses to take into account these technological advancements (Boothet al., 2021).Maternal health is a crucial aspect of public health as it directly affects the wellbeing of both mother and child.AI-based models can analyze vast amounts of health data, both structured and unstructured, to identify patients who may be at high risk for adverse outcomes.AI-based models have shown promising results in various clinical applications, including disease diagnosis, treatment planning, and patient monitoring.Pregnancy can be graded into low, moderate, and high risk based on risk factors that have been shown to contribute to the occurrence of pregnancy complications (Al-Hindi et al., 2020).Maternal and childhood mortality remains a major global health concern and a key indicator for the United Nations Sustainable Development Goal 3 (SDG 3).

Egypt had become a safer place to live and do
business, and to achieve Egypt's Vision 2030, the
country has begun to adopt artificial intelligence
and technology in various sectors. The
government is becoming more intrusive in
sparking the growth of artificial intelligence
through initiatives aimed at boost research and
development within its borders. regarding an
Egyptian society powered by artificial
intelligence and robotics, the government has set
a general target of 7.7% of Egypt's Gross
Domestic Product to be derived from artificial
intelligence and robotics by 2030 (Egypt's
Artificial Intelligence Future, 2020).Nursing
practice has become more standardized than in the
past, which requires nurses to make more important
decisions. In addition to shifting from paper to mostly
digital patient records, other tools such as wearable
technology, mobile apps, smart beds, and mobile
monitoring devices have been added to the nursing
toolkit and have been identified as significant recent
technological advancements in nursing practice. So, it
is necessary to adapt the traditional role of nurses to
take into account these technological advancements
(Boothet al., 2021).Maternal health is a crucial aspect of public health as it directly affects the wellbeing of both mother and child. Despite advances in medical science, maternal mortality remains a significant problem in many countries, particularly in developing nations (Olonade et al., 2019; Musarandega et al., 2021). Maternal and childhood mortality remains a major global health concern and a key indicator for the United Nations Sustainable Development Goal 3 (SDG 3). According to the World Health Organization (WHO), about 810 pregnant women and 6,700 newborns die every day (WHO, 2019, 2020).While most pregnancies and births are uneventful, all pregnancies
are at risk. About 15% of all pregnant women will develop a lifethreatening complication that requires specialized care, and some
will require major obstetric intervention to survive (WHO, 2019).
According to the World Health Organization (WHO), around 800
women die every day around the world from preventable causes
related to the inherent risks of pregnancy. About 295,000 women
died during and following pregnancy and childbirth in 2017. The
vast majority of these deaths (94%) occurred in low-resource
settings, and most could have been prevented (WHO, 2019).In recent years, artificial intelligence (AI) has emerged as a powerful tool in healthcare, offering new ways to analyze and interpret complex medical data. AI-based models have shown promising results in various clinical applications, including disease diagnosis, treatment planning, and patient monitoring. AI-based models can analyze vast amounts of health data, both structured and unstructured, to identify patients who may be at high risk for adverse outcomes. These models can help healthcare providers make more accurate and timely decisions; and when it refers to maternal health care in pregnancy, it can ultimately improve maternal and fetal health outcomes. AI offers novel approaches to prediction modeling, diagnosis as well as early detection of pregnancies at risk (Ramakrishnan et al., 2021). A study by Akazawa and Hashimoto (Akazawa and Hashimoto, 2022) evaluated the accuracy of AI in predicting preterm birth in pregnancy, in a bid to increase preparedness and reduce neonatal deaths. The common predictive values used were electrohysterogram images, the metabolic panels in amniotic fluid or maternal blood, obstetric ultrasound images of the cervix, and biological profiles of mothers. Also, AI has been used in predicting the onset of pregnancy conditions such as preeclampsia, and gestational diabetes mellitus, and in the management of diseases such as ectopic pregnancy (Abuelezz et al., 2022).Identifying high-risk pregnancies is a critical step in ensuring maternal and fetal health, but it can be a challenging task due to the complexity and variability of the factors involved. Maternal health risk during pregnancy refers to the likelihood of a woman experiencing adverse health outcomes during pregnancy or childbirth. Pregnancy can be graded into low, moderate, and high risk based on risk factors that have been shown to contribute to the occurrence of pregnancy complications (Al-Hindi et al., 2020).
or to the offspring such as prematurity, perinatal asphyxia, congenital anomalies and even cardiovascular abnormalities in adulthood (Majella et al., 2019; Yoon, 2021). These detrimental effects undoubtedly impose serious health risks on both the mother and the fetus. Risk factors for adverse maternal health outcomes during pregnancy can include a variety of factors such as age, pre-existing medical conditions, lifestyle factors, and socioeconomic status (Londero et al., 2019; Crear-Perry et al., 2021).Artificial Intelligence Technology (AIT) is a
branch of computer science designed to imitating of by human brain by realizing tasks or solving
problems also used in nursing care of patient, and
automating various processes, including learning
and decision-making (Maddox et al., 2019).Nowadays, the healthcare world endorses a fast
technological evolution, including emerging artificial
intelligence technology (AIT). The AIT becomes
widely used in our modern lives, specifically in
medical and nursing practice. It is likely to change the
health world and the way it works. It offers chances
and challenges for the nursing profession (Van Bulck
et al., 2023). So, nurses have to be immersed in
conceptualizing, developing, and implementing AIT.Additionally, Artificial intelligence
technologieshave the capability advance nursing
performance and make it possible for nurses to
give their patients more individualized, evidence -
based care through improvingnurses' professional
and helping in solving the problems (Abd ElMonem, 2023).
Artificial intelligence has an impact on the
roles of senior management by increasing their
creativity and strategic thinking (Ronquillo et al.,
2021).
Artificial intelligence has many
applications in healthcare, including assisting in
disease assessment, diagnosis, and solving
various clinical problems, reducing lost data,
enhancing good nursing communication skills,
improving inpatient care management, diminish
nurse workload, and improving patient safety
(Zhou et al.,2022). As well, Liu et al.
(2022),clarified
that nursing
intervention
canadvantage from AI-based medical information
processing.Perception toward artificial
intelligence is defined as the
integration of sensory impressions into
information that is psychologically
meaningful (Kundaliya et al., 2022).
Various health care professionals,
particularly clinicians, reportedly have
mixed attitudes towards AI (Abdullah
& Fakieh, 2020), and it has been
claimed that they understand neither)
how AI uses algorithms nor the inner
workings of algorithms (RomeroBrufau et al., 2020). This lack of
knowledge may increase anxiety and
arouse conflicting emotions in clinical
staff which may affect their
perceptions of AI (Abdullah & Fakieh, 2020)Attitudes toward artificial intelligence
is defined as a learned association in
memory between artificial intelligence
and a positive or negative evaluation of
artificial intelligence, and attitude
strength is equivalent to the strength of
this association (Brown, 2022). In the
context of (digital) human–machine
interaction, people are increasingly
dealing with artificial intelligence in
everyday life. Through this, we
observe humans who embrace
technological advances with a positive
attitude. Others, however, are
particularly sceptical and claim to
foresee substantial problems arising
from such uses of technology
(Sindermann et al., 2021).
Hence, nurse leaders need to foster
positive attitudes towards AI
technologies (Ronquillo et al., 2021),
and to assist AI‟s beneficial
deployment in future health care there
are clear needs to understand nurse
leaders‟ and developers‟ current
perceptions of AI. This would provide
insights into how AI could be
developed to best serve health care
organizations, clinicians‟ workflows
and patient care. Such insights would
be highly valuable for developers of
AI, health care organizations and
decision makers seeking to develop
and implement effective AI-based
solutions.Artificial intelligence refers broadly to computing
technologies which resemble processes related to
human intelligence, as reasoning, adaptation and
learning, sensory understanding and interaction
(Hassanzadeh, et al., 2018). The developing use
cases of artificial intelligence in the sector of
healthcare might be shown as technologies collection which enable machines to perceive, understand, act
and learn in order to carry out healthcare
administrative and clinical functions, in addition to be
enrolled in research and for clinical learning
activities. For the last time, Artificial intelligence has
increased productivity and its extensive widespread
into daily life is increasing at a rapid pace (Taei,2020)AI has been divided into many subdisciplines, focusing on very distinct
problems (such as vision, problem
solving, language comprehension,
learning, etc.) (Laï et al., 2020).
Artificial intelligence (AI) is also
defined as a collection of technologies
that uses complex algorithms and
software to emulate human cognition
in the analysis, interpretation and
understanding of complex healthcare
data. AI can enhance the ability for
nurses to better grasp the day-to-day
patterns and needs of their patients.
According to Eric Topol, (2019), the
promise of AI is to provide a complete,
panoramic view of an individual‟s
health information; to improve
decision making; to eliminate errors
such as misdiagnosis and unnecessary
procedures; to assist with ordering and
interpreting appropriate tests; and to
recommend treatment.The AIT includes numerous healthcare technologies
that can alter nurses’ roles and improve patients' care,
including robots, algorithms, risk prediction, speech
recognition, and clinical decision support (Robert,
2019; Pailaha, 2023).Artificial Intelligence (AI) has been
transformative for many public and
private industries, and we are currently
observing an AI-led revolution in
healthcare. AI is a fundamental
paradigm shift in healthcare that is
already affecting nurses in their
everyday work, and its impact will be
even more pronounced in the future.
AI is embedded in nurses‟ daily life as
algorithms, smart systems and in their
education. Even though AI
applications in healthcare date back to
the late 1970s, technological advances
in robotics and computing and the right
social climate have created ideal
conditions to take full advantage of
what AI can contribute to improving
the provision of care (Michalowski &
Park, 2022).
Artificial intelligence (AI) is an
umbrella term used to describe
techniques developed to teach
computers to mimic human-like
cognitive functions like learning,
reasoning, communicating and
decision-making (Robert, 2019). In
other words, AI refers to the simulation
of human intelligence in machines that
think like humans and imitate human
actions (Frankenfield, 2022).
According to the definition of Marvin
Minsky, the father of AI, AI simply
means that a machine is able to do a
task, which is considered to be an
intelligent one by human beings.
Indeed, AI is a discipline for which the
applications fall into two categories:
(1) the attempt to reproduce the
capabilities of the human mind and 2)
the creation of tools to carry out tasks,
which today need a human action.Artificial intelligence technologies have the
skill to advance nursing practice and make it
possible for
medical surgical nurses
togivetheirpatients more individualized,
evidence -based care throughincreasemedical
surgical nurses' professional personality and
approvingin answer the problems. To achieve
a competitive better in the labor market,
there is a need to radical change to
digitalize healthcare sectors. From this
point, artificial intelligence has completed to
take the attention of key healthcare top
managers and providers who are currently
experiencing a dilemma of whether or not to
fully or partially integrate it into their work
(Elsayed&Sleem, 2021). The advancement of
artificial intelligence technology to additional
adoption and value across health care is
perpetuated by cost, quality, care outcomes,
and support to analyze large amounts of
data efficiently. However, few inquiries have
investigated nurses’ educational intervention
regarding artificial intelligence technology
(Shaik, 2020).AI could be used in nursing information
systems through monitoring client’ information,
helping to remember patient data, reporting forms,
managing quality and minimizing hospitalization
time, enhancing care efficacy and performing
interventions in its correct time, cost-effective and
time saving, and helping in documentation of
patient in formation. However, there are many
barriers facing AI systems application for nursing
as elevated costs of the system, and the continuous
updates (Mehdipour, 2019). Nursing managers
play a very important role in advocating for the
objective and the most efficient application of AI
health solutions. To accomplish this role and duty,
nurses with strong professional identity must be
aware of the extensive spread of AI and the effect
of development, deploying and evaluation of these
technologies (Risling & Low, 2019).The replication of
cognitive abilities in humans is a common aspect
of AI. From the health care perspective, AI is a
"paradigm change in health care, propelled by
rising availability of health care data and quick
progress of analytics techniques. The main
categories of applications include diagnosis and
treatment (Davenport & Kalakota, 2019;
Elsayed & Sleem, 2021).Artificial intelligence is being used in
nursing information systems to monitor
client data, maintain patient data, manage
quality, enhance care efficacy, and document
patient information. However, challenges
include technological limitations, increased
system costs, and ongoing upgrades. These
obstacles hinder the effective implementation
of AI-based decision support systems innursing, requiring ongoing improvements
and cost-effectiveness (Mehdipour, 2019)The progress of AI as a mechanism for
develop health care provides ways to
raise the quality of health care services,
provide
unexpected chances to
development patient outcomes,
decrease prices, and influence human
health and it will enable a sustainable
healthcare system (Tran et al., 2019 &
Matheny et al., 2019). AI is likely to
promote robotics and it can provide
relevant information synthesis and
recommendations to patients, families,
and the health care team (Israni &
Verghese, 2020). AI can be defined as
the capability of a computer to achieve
tasks that usually linked with
intelligent beings (Copeland, 2020 &
Hanna et al., 2021).
The progress of technology and digital
transformation has facilitated the
growth of AI to support health care
systems. AI technologies have been
used in nursing profession for long
years, but not recognized as AI. AI
implements in nursing such as;
scientific decision support, mobile
health and sensor-based technologies,
and voice helpers and robotics.
However, the rising interest in AI in
healthcare setting is associated with
new discussions on the relationship
between AI and nursing. Nurses’ must
be involved in directing the growth and
use of AI technologies in the health
care settings. So, there is a necessity
for the nursing profession to participate and well understand of AI (He et al.,
2019 & European Commission, 2019).In addition to offering an insight into an enhanced
and improved digital future, the rapid introduction of
(AI) into the healthcare system has also created
serious concerns about this evolution social and
ethical consequences. Nursing managers play a very
important role in advocating for the objective and the
most effective use of AI health solutions. To
accomplish this role and duty, nurses need to be
informed on the extensive spread of AI and the effect
of development, deployment and evaluation of these
technologies (Risling & Low, 2019)Therefore, there is no
doubt that the impact of AI in nursing practice
will be transformative. An example of the
application of artificial intelligence in nursing
practice is the use of robots in drug dispensing,
bots for special needs and decision-making
applications for nursing diagnosis, planning and
intervention(Booth et al., 2021).