The data to decision path for infusion of AI in healthcare

Beginner Level
8 hours to complete
Flexible Schedule

Jiban Khuntia

What You’ll Learn

Understand AI’s role in the Data-Information-Analysis-Decision (DIAD) process and how it enhances decision-making in healthcare.

Analyze the integration of AI-driven analytics and machine learning algorithms in healthcare models for predictive and operational intelligence.

Assess the challenges of AI implementation in healthcare, including data governance, workflow integration, and strategic alignment.

Skills You’ll Gain

Machine Learning Methods Artificial Intelligence Clinical Informatics Artificial Intelligence and Machine Learning (AI/ML) Health Informatics Advanced Analytics Data-Driven Decision-Making Decision Intelligence Predictive Analytics Analytics AI Enablement AI Integrations Data Governance Machine Learning Predictive Modeling Machine Learning Algorithms Artificial Neural Networks Applied Machine Learning

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There are 4 modules in this course

Covers how AI supports the DIAD pipeline, from raw data to informed healthcare decisions.

Focuses on the centrality of analytics in transforming data into actionable insights for healthcare.

Introduces fundamental AI and machine learning algorithms widely used in healthcare applications.

Explores advanced AI algorithms designed for complex healthcare modeling challenges.