By the end of this CPD-certified course, learners will be able to:

♦ Define and explain key AI concepts and technologies relevant to healthcare.

♦ Identify real-world AI applications across clinical, community, and case work settings.

♦ Apply AI in early detection, remote monitoring, and predictive analytics.

♦ Collaborate with AI systems to improve patient care, triage, and workflow efficiency.

♦ Understand ethical, legal, and cultural implications of AI in healthcare.

♦ Design and propose AI-for-good solutions that address challenges in education, health, environment, or community wellbeing.

♦ Protect data privacy and advocate for patient autonomy when using AI tools.

♦ Critically assess AI decision-support systems and integrate them responsibly in practice.

♦ Envision future innovations and their impact on professional roles and responsibilities.

By the end of this course, learners will be able to:

♦ Define foundational AI concepts and describe their relevance in modern healthcare systems.

♦ Recognize and evaluate AI applications in diagnostics, patient monitoring, treatment planning, and
healthcare management.

♦ Utilize AI tools for early disease detection, risk assessment, and clinical decision support.

♦ Work collaboratively with AI systems to enhance care delivery, workflow efficiency, and patient triage.

♦ Navigate ethical and legal frameworks related to AI in healthcare, including issues of bias, equity, and cultural sensitivity.

♦ Ensure data privacy and patient consent when using AI-driven technologies in clinical settings.

♦ Assess the reliability and limitations of AI systems in real-time healthcare scenarios.

♦ Design and propose AI-driven solutions for real-world challenges in health, wellness, and public care.

♦ Anticipate emerging trends and prepare for future roles where AI will be integral to healthcare delivery.

Module 1: INTRODUCTION TO AI IN HEALTHCARE

♦ Understand foundational AI concepts.

♦ Distinguish AI from traditional tools.

♦ Explore core technologies like ML, NLP, and computer vision.

♦ Reflect on how AI impacts your healthcare role.

Module 2: TRANSFORMING PATIENT CARE WITH AI

♦ Explain AI’s role in early detection, remote monitoring, and predictive care.

♦ Analyze real-time applications in Canadian and global settings.

♦ Describe how AI enhances patient safety, access, and personalized care.

Module 3: PRACTICAL IMPLEMENTATION AND ETHICAL CONSIDERATIONS

♦ Implement AI tools into clinical workflows and service delivery models.

♦ Uphold ethics, consent, and transparency in AI-driven environments.

♦ Safeguard patient data privacy and follow Canadian regulatory standards.

Module 4: YOUR ROLE IN AI-DRIVEN HEALTHCARE

♦ Collaborate with AI in decision-making.

♦ Use AI support tools responsibly.

♦ Prepare for AI-driven innovations and future-ready healthcare practices.

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