Course Outline

Introduction to AI in Healthcare

  • Overview of AI applications in medical diagnostics
  • AI-powered patient monitoring and decision support
  • Regulatory and ethical considerations

AI for Medical Image Analysis

  • Deep learning techniques for medical imaging
  • Automating radiology and pathology workflows
  • Hands-on: Implementing AI for medical image classification

Predictive Analytics and AI for Diagnostics

  • Using AI for disease prediction and early diagnosis
  • AI models for risk assessment and prognosis
  • Hands-on: Building predictive models with patient data

AI Integration with Electronic Health Records (EHR)

  • Standardized healthcare data formats (FHIR, HL7)
  • Automating clinical workflows with AI
  • Hands-on: Connecting AI models to EHR systems

AI for Drug Discovery and Personalized Medicine

  • How AI accelerates drug discovery and development
  • AI-driven precision medicine and treatment recommendations
  • Case studies of AI in pharmaceutical research

Compliance, Security, and Ethical AI in Healthcare

  • Ensuring HIPAA and GDPR compliance
  • Bias mitigation and fairness in AI-driven healthcare
  • Security best practices for AI healthcare applications

Implementing AI Solutions in Healthcare

  • Challenges and best practices for AI deployment
  • Scaling AI solutions in hospitals and clinics
  • Hands-on: Deploying an AI-powered healthcare assistant

Summary and Next Steps

Requirements

  • Basic knowledge of AI and machine learning concepts
  • Experience with data analysis and healthcare systems
  • Familiarity with medical terminology and diagnostics

Audience

  • Healthcare professionals
  • AI developers
  • Medical researchers
 14 Hours

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