CURRENT INSIGHTS AND INTERPRETATION OF WORLDWIDE APPLICATIONS OF AI IN

NURSING
“Artificial Intelligence is not a substitute for human intelligence; it is a tool to amplify human creativity
and ingenuity.”
Fei-Fei Li
Co-Director of the Stanford Institute for Human-Centred Artificial Intelligence & IT Professor at the
Graduate School of Business

What is AI?
AI is the science of making machines that can think like humans.
It can do things that are considered “smart”.

Who is the father of AI?

John McCarthy is considered as the father of AI. An American Computer Scientist & Cognitive
Scientist, California, US.
Importance of Artificial Intelligence in everyday life?
AI has been transforming various industries and aspects of modern life, from healthcare to
entertainment, and from transportation to education. The impact of AI is vast and it has become an
essential part of our everyday lives. The impact of AI in our lives are as follows:
i. AI in healthcare-AI are providing more accurate diagnoses, and effective
treatments. AI used to develop new drugs & personalised treatments, leading
to targeted care.

ii. AI in entertainment- Streaming services like Netflix, Spotify uses

recommendation algorithms to suggest content based on browsing and buying
history. Also, in gaming industry, AI is used to create realistic characters and
environments like PUBG.

iii. AI in transportation- Google map & Waze analyse real time traffic data &
provide faster route.
iv. AI in cybersecurity is playing a crucial role in detecting, preventing cyberattacks
in real time, also monitor social media, identify fake news and prevent phishing
attacks.
a. Email filtering- Filter out spam, emails, categorising incoming emails as
primary, social, promotion, etc.
b. Security & fraud detection- Fraudulent activity in banking & online
transactions, home security systems through facial recognition
technology.
v. AI as personal assistants:
a. AI powered digital assistants on smartphones like Siri, Google
Assistant, Alexa, or Bixby can help manage daily tasks, set reminders,
etc.
b. Online shopping- provides personalised recommendations based on
browsing & buying history.
What are the AI programmes/tools that are used in healthcare?
a) Machine Learning
b) National Language Processing
c) Convolutional Neural Network
 In recent years, the integration of artificial intelligence (AI) into various sectors has
revolutionized industries, and healthcare is no exception. Among the many facets of healthcare,
nursing plays a crucial role in patient care, and the incorporation of AI has the potential to enhance
and streamline nursing practices. However, while AI offers promising possibilities, there are also
notable pitfalls that must be carefully considered and navigated.

In the nursing setting, the advancement of AI technology is being greeted with excitement as
a promising nursing innovation. AI technologies may be able to improve the nursing care of various
health conditions, provide complete information to support decision-making, manage medical
records, minimize medical errors, optimize nursing care processes, make healthcare more
accessible, provide better patient experience, improve nursing care outcomes, and reduce per
capita healthcare costs. However, one of the potential implications of replacing aspects of human
expertise with autonomous AI system technology is the legal implications of clinical accountability.

a) APPLICATION OF AI IN NURSING PRACTICE

The integration of AI in nursing holds immense promise for revolutionizing patient care. AI-
powered technologies can assist nurses in numerous ways, optimizing clinical workflows and
decision-making processes.
i. The use of AI for predictive analytics, which can help identify patients at risk of deteriorating
health conditions. By analysing vast amounts of patient data, AI algorithms can recognize
patterns and alert nurses to potential issues before they become critical, enabling proactive
interventions and improved patient outcomes.
ii. Diagnosis and treatment planning: AI can support nurses in making accurate diagnoses by
analysing complex medical data, such as medical images and test results. This can
significantly reduce human errors and enhance diagnostic accuracy.
iii. AI-driven treatment recommendations can provide nurses with evidence-based insights,
ensuring that patients receive the most appropriate care tailored to their individual needs.
iv. AI-powered virtual assistants and chatbots also hold the potential to improve patient
engagement and education. These tools can provide patients with accurate medical
information, answer queries, and offer guidance on post-discharge care. By empowering
patients with knowledge, nurses can focus on more critical aspects of care while fostering
patient autonomy and well-being.
v. Cancer: AI applications in Oncology include risk assessment, early diagnosis, patient
prognosis estimation, treatment selection based on deep knowledge. ML has been highly
effective at predicting various types of cancer, including breast, brain, lung, liver and prostate
cancer. These technologies have the potential to improve the diagnosis, prognosis and QOL
of patients.
vi. Neurology: AI system to restore the control of movement in patients with quadriplegia. AI
tested the power of an offline man/machine interface that uses the discharge timings of spinal
motor neurons to control upper-limb prostheses.
vii. Cardiology: Potential application of the AI system to diagnose the heart disease through
cardiac image. AI used to provide automated, editable ventricle segmentations based on
conventional cardiac MRI images.
viii. Eye: Analysed the ocular image data to diagnose congenital cataract disease. AI used to
detect referable diabetic retinopathy through the retinal fundus photographs.

Other applications are:

a) Classical ML constructs data analytical algorithms from data. A patient’s traits commonly
include baseline data, such as age, gender, disease history and so on, and disease-specific
data, such as diagnostic imaging, gene expressions, EP test, physical examination results,
clinical symptoms, medication to construct algorithms.

b) CNN was used to diagnose congenital cataract disease through learning the ocular images
to detect referable diabetic retinopathy through the retinal fundus photographs.
c) Use of NLP for reading the chest X-ray reports to alert physicians for the possible need for
anti-infective therapy, monitor the laboratory-based adverse effects, help with disease
diagnosis.
d) Stroke is a common and frequently occurring disease that In recent years, AI techniques
have been used in more and more stroke-related studies. Below we summarise some of the
relevant AI techniques in the three main areas of stroke care: early disease prediction and
diagnosis, treatment, as well as outcome prediction and prognosis evaluation. Stroke is a
chronic disease with acute events. Stroke management is a rather complicated process with
a series of clinical decision points.
e) Currently, many critical care indices are not captured automatically at a granular level, rather
are repetitively assessed by overburdened nurses. In this pilot study, we examined the
feasibility of using pervasive sensing technology and artificial intelligence for autonomous
and granular monitoring in the Intensive Care Unit (ICU). As an exemplary prevalent
condition, we characterized delirious patients and their environment. We used wearable
sensors, light and sound sensors, and a camera to collect data on patients and their
environment. We analysed collected data to detect and recognize patient’s face, their
postures, facial action units and expressions, head pose variation, extremity movements,
sound pressure levels, light intensity level, and visitation frequency. We found that facial
expressions, functional status entailing extremity movement and postures, and
environmental factors including the visitation frequency, light and sound pressure levels at
night were significantly different between the delirious and non-delirious patients. Our results
showed that granular and autonomous monitoring of critically ill patients and their
environment is feasible using a non-invasive system, and we demonstrated its potential for
characterizing critical care patients and environmental factors.
f) Current State of AI Systems in Health Care: Prevalence of AI Systems in Use Respondents
named 12 different medical fields or specialties in which AI algorithms have been developed
for clinical practice: neurology, oncology, radiology, dermatology, cytomorphology, surgery,
paediatrics, pathology, ophthalmology, urology, genomics, and diabetology, as well as
intensive care medicine.
g) AI systems for radiology: Classification of medical imaging was often mentioned as a relevant
use case, again potentially highlighting the maturity of this application. For instance, current
AI systems can also use text-based data from electronic health records (EHRs) to make
medical predictions using natural language processing. AI algorithms are also used to
optimize administrative tasks such as staff scheduling and billing.
h) AI algorithms could enable truly personalized health care by analysing multiple sources of
health data simultaneously and across time. For instance, long-term EHRs could be
combined with vital signs recorded via digital devices and analysed using an algorithm. Long-
term integrated data analysis could potentially facilitate the early detection of previously
hidden disease patterns and provide individualized prevention and treatment plans.

i) The use of speech recognition technology can speed up the process and/or improve
accuracy, efficiency, reduce errors, and shorten the time it takes to complete nursing
documentation.
 j) Machine learning has five algorithms and visualizes the best model using nomograms and
web calculators to help nurses assess patients’ cancer status and machine learning has
reduced in-hospital mortality using early warning scores.
k) Artificial Intelligence (AI) based chatbot services could make a difference through chat or
natural language conversation with the patient over messaging apps, web-based services,
or through telephonic conversation. Artificial Intelligence (AI) based chatbot is considered
one of the advanced ways of human-machine interactions. Chatbot services aid in health
promotion, disease prevention, and health education. Patients can have better interaction
and experience with the caregivers through the chatbot. The nursing managers need to be
aware of the chatbot services as these managers are the link between the hospital
management and the healthcare user groups. While there was moderate awareness of AI-
based chatbot services among the nursing ward managers, there was poor awareness
regarding chatbot services providing health services to patients through texting remotely,
displaying medical results, and giving advice to the patient through an appropriate specialist.
The moderate awareness about AI-based chatbot services among nursing managers
necessitates the development of an orientation program for nursing staff on the benefits of
chatbots to patients and a plan to develop efficient healthcare chatbots with comprehensive
features to enable better patient care.
a. Customizing chatbot, to include politeness for efficient interaction will surely lead to a
pleasant patient experience.
b. Various possibilities of a chatbot technology include health related patient surveys,
healthcare-related reminders to users, interaction with physicians, appointment
booking, and receiving health data.

b) AI IN NURSING POLICY & ADMINISTRATION

In nursing policy and administration, AI technologies can streamline administrative work,

optimize resource allocation, and improve organizational efficiency.
i. AI-powered systems analyze healthcare data to identify areas for improvement and provide
policymakers with evidence-based information. They can also automate routine tasks like
appointment scheduling and financial management, allowing nurses to focus on direct patient
care. However, implementing AI in nursing policy and administration requires addressing
challenges related to data governance, interoperability, and workforce readiness.
Collaboration between policymakers, healthcare leaders, and technology developers is
crucial to fully harness AI's capabilities while minimizing risks and ensuring ethical and
equitable integration into nursing practice and administration.
ii. The most significant opportunity for using AI systems in health care is the reduction in
workload. For instance, outsourcing time-consuming and repetitive tasks to an AI system
would allow HCWs to focus on more complex tasks and patient interactions.

c) AI IN NURSING EDUCATION

The impact of AI on nursing education is of great importance.

i. It exerts its influence on curriculum design and instructional methodologies. The integration
of virtual simulations and AI-driven educational tools provides nursing students with
immersive learning experiences.
ii. AI is capable of assessing students' clinical skills and identifying areas of knowledge gaps,
thereby enabling customized educational interventions.
iii. AI technologies grant access to the most current information and evidence-based practices,
thereby fostering continuous learning and professional development.
iv. There are challenges that need to be addressed, such as the necessity for faculty training,
investment in infrastructure, and the ethical use of AI within educational environments.
 Nursing educators must adeptly navigate these changes in order to fully leverage the benefits
of AI in enhancing the quality and effectiveness of nursing education.
v. adding nursing informatics into the nursing curriculum with courses that include data literacy,
technological literacy, systems thinking, critical thinking, genomics and AI algorithms, ethical
implications of AI, and analysis and implications of big data sets.

d) AI IN NURSING RESEARCH

AI-driven technologies have unparalleled capabilities in data analysis, predictive modelling, and decision
assistance, empowering researchers to extract important insights from extensive healthcare data.
i. AI can aid researchers in several aspects of academic writing, including as doing literature reviews,
analyzing data, and even producing initial drafts. This can accelerate research cycles and improve
the overall quality of scholarly work.
ii. Algorithms powered by artificial intelligence can assist in detecting areas of research that need
attention, proposing possible approaches for conducting studies, and promoting cooperation among
researchers from other fields.
iii. The importance of ethical considerations regarding data privacy, algorithmic bias, and the proper
utilization of AI technologies cannot be overstated. Moreover, there is a possible danger of
excessively depending on AI systems, which could undermine the development of critical thinking
abilities and creativity in academic pursuits. Achieving a harmonious equilibrium between utilizing the
advantages of AI and safeguarding the authenticity and human-centered principles of healthcare
research is crucial in fully realizing the capabilities of AI in developing nursing and healthcare studies.

Countries Pioneering in application of AI in healthcare settings

a) Asia:
i. In Japan
• RIBA (Robot for Interactive Body Assistance) used for assist with lifting and
moving patients in health care settings.
• PEARL robot, which has many sensors that help in navigation, recognition of
audio and video input as well as touch screen interface, serves to remind
people about routine activities and guide elderly through their environment.
ii. In China
• Sanbot robot that can assist nurses by providing medication reminder.
• Pudutech’s Nursing Robot assist in lifting and transferring patient and
delivering medicines.
iii. In Europe:
• Robot Assisted care: Netherland, Denmark and Germany are experimenting
with robots designed with tasks such as lifting and transferring patient,
delivering medications, and providing companionship to older adults in
Nursing homes and hospitals.
• Telepresence robots equipped with cameras which aids in remote
communication with patients, their families and health care personnel.
• Exoskeleton is used in Sweden and France exploring the use of exoskeleton
in healthcare settings to support nursing staff and improve workforce
ergonomics.
• In UK use of AI is being explored in tasks such as medication delivery, lifting
and transferring patient, and monitoring of vital signs.
Conclusion
Overall the interpretation of AI application in Nursing globally emphasizes its potential to
revolutionize healthcare delivery, enhance patient outcomes, and empower nursing professional to
thrive in a rapidly evolving digital landscape.
Can AI replace human beings?????
AI cannot replace human beings but human beings can create wonders through AI