Prof. Maria Santos
Digital Health Chair · University of Lisbon
Healthcare Innovation · Digital Health
AI Training
AI for Healthcare
Clinical systems, predictive analytics, and digital health transformation.
Overview
Healthcare organizations face unique constraints: privacy, clinical safety, and interoperability. This course covers AI applications across diagnostics support, operations optimization, patient engagement, and predictive analytics — with emphasis on EU regulatory context, clinical validation, and implementation playbooks.
Curriculum
Week 1 — AI in Clinical & Operational Context
- Digital health landscape
- Data governance in healthcare
- Use-case prioritization
Week 2 — Predictive Analytics & Decision Support
- Risk stratification
- Readmission models
- Clinical decision support basics
Week 3 — Workflow Automation & Patient Engagement
- Administrative automation
- Patient communication AI
- Interoperability considerations
Week 4 — Validation & Responsible Deployment
- Clinical validation frameworks
- Bias and safety review
- MDR / GDPR awareness
Week 5 — Capstone: Healthcare AI Blueprint
- Implementation roadmap
- Stakeholder alignment
- Pilot design
Learning Outcomes
- Healthcare-specific AI use-case portfolio
- Predictive analytics prototype with documented assumptions
- Compliance-aware deployment checklist
- Micro-Degree pathway eligibility
Skills Covered
Clinical Informatics
Predictive Health Analytics
Digital Health Strategy
Healthcare Data Governance
Expert Instructors
Learn from verified industry practitioners and professors from the Praktix expert network.
Thomas Berg
Healthcare Consultant · Charité Berlin
Clinical Informatics · Digital Health
Dr. Elena Richter
AI Research Lead · TU Munich
Machine Learning · AI Systems
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