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Galen College -AID 1080 Complete Final Exam Review(With Solutions).

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GALEN COLLEGE OF NURSING
Course Code: AID 1080
Instructor:
Date: 2026

FINAL EXAM – INTRODUCTION TO ARTIFICIAL
INTELLIGENCE AND DIGITAL



Multiple Choice (MCQ)
Which AI application is most beneficial for predicting patient deterioration in
hospital settings?
A) Natural Language Processing
B) Predictive Analytics
C) Robotics Process Automation
D) Virtual Reality
Answer: B
Rationale: Predictive analytics uses data to forecast patient outcomes,
essential in acute care to prevent deterioration.

Which digital health technology is primarily used for automated medication
dispensing?
A) Electronic Health Records (EHR)
B) Clinical Decision Support Systems (CDSS)
C) Robotic Medication Dispensers
D) Telemedicine Platforms
Answer: C
Rationale: Robotic medication dispensers automate the preparation and
delivery of medications, reducing errors.

Machine Learning algorithms in AI assist nursing by:
A) Replacing nurses during patient interviews
B) Identifying patterns in large healthcare datasets
1

,C) Performing surgical procedures autonomously
D) Administering intravenous fluids
Answer: B
Rationale: Machine learning helps analyze big data to identify trends that can
guide nursing care.

Which AI concept enables virtual assistants to understand and respond to
spoken language?
A) Computer Vision
B) Natural Language Processing (NLP)
C) Neural Networks
D) Reinforcement Learning
Answer: B
Rationale: NLP allows AI systems to interpret human speech, useful in virtual
nurse assistants.

What is a major ethical concern regarding AI in nursing care?
A) Increased workload
B) Data privacy and patient confidentiality
C) Cost reduction
D) Faster diagnosis
Answer: B
Rationale: Protecting patient data from misuse is a critical ethical issue with
AI deployment.

True/False
True or False: AI systems can fully replace clinical judgment in nursing.
Answer: False
Rationale: AI assists but does not replace clinical expertise and decision-
making by humans.

True or False: Digital health records improve interdisciplinary communication
among healthcare providers.
Answer: True
Rationale: EHR systems support real-time sharing of patient data improving
care coordination.

True or False: AI algorithms require continuous training on updated data to
maintain accuracy.
Answer: True
Rationale: AI models must be updated to reflect current trends and avoid
obsolescence.

2

, True or False: Telehealth reduces the need for any in-person nursing care.
Answer: False
Rationale: Telehealth complements but does not fully substitute direct
nursing interventions.

True or False: AI-powered clinical decision support can sometimes lead to
alert fatigue in nurses.
Answer: True
Rationale: Frequent non-critical alerts may overwhelm nurses causing
desensitization.

Short Answer
Define Clinical Decision Support Systems (CDSS) and explain their role in
nursing.
Answer: CDSS are AI-driven tools that provide nurses with evidence-based
recommendations to enhance clinical decisions, reducing errors and
improving patient outcomes.
Rationale: CDSS integrates patient data with medical knowledge to support
nursing practice.

Explain how AI can improve patient monitoring in intensive care units (ICUs).
Answer: AI can analyze continuous data streams such as vital signs,
detecting subtle changes indicating deterioration earlier than manual
observation.
Rationale: Timely AI alerts enable proactive interventions in critical settings.

List two challenges nurses might face when adapting to digital health
technologies.
Answer: Resistance to change and lack of adequate training are common
challenges.
Rationale: Successful technology adoption requires user readiness and skill
development.

What is 'big data' in healthcare and why is it important for AI?
Answer: Big data refers to large, complex health datasets collected from
diverse sources. It is important because AI algorithms need extensive data
for training and accurate predictions.
Rationale: Healthcare AI relies on big data to identify meaningful patterns.

Briefly describe the function of natural language processing (NLP) within
nursing documentation.
Answer: NLP converts unstructured free-text nursing notes into structured
data for easier analysis and decision support.
3

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