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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
Testimonials (1)
Trainer responding to questions on the fly.