Do the planners or presenters have any relevant financial relationships to disclose?

<text variant="body1">No. The planners and presenters for this educational activity do not have relevant financial relationships with ineligible companies that produce, market, sell, resell, or distribute healthcare products used by or on patients. <text variant="body1">If a relevant financial relationship exists, the disclosure will identify the individual’s name and role, the company involved, and confirm that the relationship has been reviewed and mitigated.

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Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Evaluating AI in Nursing Practice

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Evaluating AI in Nursing Practice

Dieser Kurs ist Teil von Spezialisierung „AI in Nursing Practice: Foundations for Quality and Safety“

Dozenten: Kais Gadhoumi

Bei Mehr erfahren enthalten

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

3 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

3 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Explain how AI models learn from historical healthcare data.
Interpret common AI outputs with appropriate confidence and skepticism.
Identify situations where AI tools may perform poorly.
Recognize how bias can emerge from historical data and healthcare system patterns.

Kompetenzen, die Sie erwerben

Kategorie: Nursing Practices
Kategorie: Nursing Process
Kategorie: Artificial Intelligence and Machine Learning (AI/ML)
Kategorie: Nursing
Kategorie: Nursing and Patient Care
Kategorie: Healthcare Ethics
Kategorie: Artificial Intelligence

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Kürzlich aktualisiert!

September 2026

Bewertungen

8 Aufgaben

Unterrichtet in Englisch

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

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Erweitern Sie Ihre Fachkenntnisse

Dieser Kurs ist Teil der Spezialisierung Spezialisierung „AI in Nursing Practice: Foundations for Quality and Safety“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

Lernen Sie neue Konzepte von Branchenexperten
Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 4 Module

This course helps nurses read AI outputs critically, weighing what shaped them, where they're likely to fall short, and what they can and can't tell you about the patient in front of you. Through the four-bucket framework and an AI-powered discussion activity, learners will practice tracing an AI output back to the training data and process that produced it, interpreting outputs with the right mix of confidence and skepticism, and recognizing bias as a predictable pattern that shows up when training data doesn't fully reflect the patients a tool serves.

In support of improving patient care, Duke University Health System Clinical Education and Professional Development is accredited by the American Nurses Credentialing Center (ANCC), the Accreditation Council for Pharmacy Education (ACPE), and the Accreditation Council for Continuing Medical Education (ACCME), to provide continuing education for the health care team. The designation was based upon the quality of the educational activity and its compliance with the standards and policies of the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC). Duke University Health System Department of Clinical Education and Professional Development designates this activity for up to 9 credit hours for nurses. Nurses should claim only credit commensurate with the extent of their participation in this activity. Upon completion of all three courses (Seeing AI in Nursing Practice, Evaluating AI in Nursing Practice, and Applying AI in Nursing Practice) in the AI in Nursing Practice: Foundations for Quality and Safety Specialization, you will be eligible to apply for continuing education credits. Please note that continuing education credit rosters will be collected quarterly.

Before you can evaluate an AI output, it helps to understand how the model behind it was developed. This module introduces how AI systems learn from data, including the roles of training, labels, and different learning approaches. You’ll consider how these choices shape what a model can recognize, what it may miss, and how its outputs should be interpreted.

Das ist alles enthalten

2 Videos8 Lektüren2 Aufgaben

2 VideosInsgesamt 11 Minuten

Evaluating AI in Nursing Practice3 Minuten
How AI Learns from Data8 Minuten

8 LektürenInsgesamt 31 Minuten

Welcome to Evaluating AI2 Minuten
Map of Four Things AI Does in Your Workflow5 Minuten
Meet Your Instructors2 Minuten
Lesson Overview2 Minuten
A Closer Look into How AI Learns5 Minuten
Term Spotlight: Supervised, Self-Supervised Learning, and Large Language Models5 Minuten
Term Spotlight: Unsupervised Learning and Semi-Supervised Learning5 Minuten
Inside MEWS5 Minuten

2 AufgabenInsgesamt 10 Minuten

Recognizing Training, Labels, and Learning5 Minuten
Recognizing the Four Learning Types5 Minuten

This module follows the path from clinical documentation to the output that appears on your screen. Along the way, you’ll develop vocabulary to help you interpret AI outputs thoughtfully by understanding what they may tell you, what they may leave out, and when to approach them with additional questions.

Das ist alles enthalten

2 Videos8 Lektüren3 Aufgaben

2 VideosInsgesamt 14 Minuten

From Chart to Risk Score7 Minuten
What to Expect From AI Outputs7 Minuten

8 LektürenInsgesamt 34 Minuten

Lesson Overview2 Minuten
Term Spotlight: Structured Data, Unstructured Data, and Natural Language Processing5 Minuten
Term Spotlight: Features and Labels5 Minuten
Inside LACE5 Minuten
Lesson Overview2 Minuten
A Closer Look at AI Outputs5 Minuten
Term Spotlight: Sensitivity and Specificity5 Minuten
Inside the Morse Fall Scale and Hendrich II5 Minuten

3 AufgabenInsgesamt 15 Minuten

Recognizing the Building Blocks of a Risk Score5 Minuten
Recognizing The Four Types of AI Outputs5 Minuten
Recognizing Sensitivity and Specificity5 Minuten

Understanding how AI systems work is one part of evaluating their outputs. This module explores the conditions that can make AI tools less reliable and introduces bias as a predictable pattern that may affect how models perform across different patient populations.

Das ist alles enthalten

2 Videos5 Lektüren2 Aufgaben

2 VideosInsgesamt 15 Minuten

Where AI Struggles and Why9 Minuten
Bias in AI Systems7 Minuten

5 LektürenInsgesamt 22 Minuten

Lesson Overview2 Minuten
Where AI Struggles In Your Workflow5 Minuten
Inside the Braden Scale5 Minuten
A Closer Look into Bias in AI Systems5 Minuten
Inside the Epic Sepsis Model5 Minuten

2 AufgabenInsgesamt 10 Minuten

Recognizing Where AI Struggles5 Minuten
Recognizing Bias in AI Systems5 Minuten

This module closes the course and hands the learning back to you. You'll apply the evaluative vocabulary from this course to a real tool from your own workflow before completing the final assessment.

Das ist alles enthalten

4 Lektüren1 Aufgabe

Erwerben Sie ein Karrierezertifikat.

Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.

Dozenten

Kais Gadhoumi

Duke University

3 Kurse17 Lernende

von

Duke University

Mehr von Patient Care entdecken

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AI in Nursing Practice: Foundations for Quality and Safety
Spezialisierung
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Seeing AI in Nursing Practice
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Kategorie: Vorschau

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Häufig gestellte Fragen

Duke University Health System Department of Clinical Education and Professional Development designates this activity for up to 9 credit hours for nurses. Nurses should claim only credit commensurate with the extent of their participation in this activity.

Upon completion of all three courses (Seeing AI in Nursing Practice, Evaluating AI in Nursing Practice, and Applying AI in Nursing Practice) in the AI in Nursing Practice: Foundations for Quality and Safety Specialization, you will be eligible to apply for continuing education credits. Please note that continuing education credit rosters will be collected quarterly.

No. The planners and presenters for this educational activity do not have relevant financial relationships with ineligible companies that produce, market, sell, resell, or distribute healthcare products used by or on patients.

If a relevant financial relationship exists, the disclosure will identify the individual’s name and role, the company involved, and confirm that the relationship has been reviewed and mitigated.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.