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100% fundable

AI+ Doctor™

Those working in medicine who want to understand how AI is changing diagnostics, documentation, and decision-making will find targeted, practical knowledge here. The content connects everyday clinical reality with current technologies – directly applicable from day one.

Key topics

  • AI methods supporting clinical diagnostic models.
  • Analysis of medical information using smart algorithms.
  • Predictive models for planning treatment pathways.
  • Digital tools for efficient medical documentation.
  • Data protection and security requirements in clinical AI use.

Prerequisite
Knowledge of basic medical processes and an interest in digital applications provide a solid starting point.

Target group
Physicians, researchers, and healthcare management professionals who want to integrate AI safely and effectively into their work.

Sound AI understanding and clinical practice complement each other – creating the foundation for more precise care, robust analyses, and a sustainable approach to modern medicine.
 

course content
  • From diagnostic support to clinical decision intelligence
  • What makes AI unique in medicine
  • Types of machine learning in healthcare
  • Common algorithms and their clinical function
  • Practical use cases across medical specialties
  • Clearing up misconceptions about AI in healthcare
  • Real tools clinicians use today
  • Case study: Medical image analysis with MediScan AI
  • Understanding neural networks: foundations of AI performance
  • CNNs for visual data: how AI reads medical images
  • Image modalities in medical AI
  • Model training: from data labeling to deployment
  • Human-AI collaboration in diagnosis
  • FDA-approved AI tools in diagnostic imaging
  • Hands-on exercise: AI-assisted differential diagnosis with Symptoma
  • Clinical data types: EHRs, vital signs, laboratory results
  • Structured vs. unstructured data in medicine
  • Dashboards and visualization for clinical decisions
  • Pattern recognition and signal detection in patient data
  • Identifying high-risk patients using trends and AI scores
  • Interactive exercise: AI assistant for clinical notes
  • Predictive models for risk stratification – sepsis and readmissions
  • Logistic regression, decision trees, ensemble methods
  • Real-time alerts – early warning systems (MEWS, NEWS)
  • Sensitivity vs. specificity – selecting metrics for clinical needs
  • AI-driven interventions in the ICU and emergency room
  • NLP foundations in healthcare
  • Large language models in medical practice
  • Prompt engineering in a clinical context
  • Generative AI for summaries, scripts, and translations
  • Ambient intelligence: next-generation documentation
  • Limitations and risks of NLP in medicine
  • Case study: Clinical documentation with Nabla Copilot
  • Algorithmic bias – effects on race, gender, and socioeconomic status
  • Explainability and transparency (SHAP, LIME)
  • Validating AI across different population groups
  • Regulatory standards – HIPAA, GDPR, FDA/EMA compliance
  • Developing ethical guidelines for AI use
  • Case study: Biased pulse oximetry detection
  • Understanding and interpreting core metrics
  • Reading confusion matrices and ROC curves
  • Adapting metrics to the clinical context
  • Using AI results to support better clinical decisions
  • Critically reviewing manufacturer claims
  • Recognizing warning signs in commercial AI tools
  • Checklist: questions to ask before deploying AI tools
  • Practical exercises
  • Identifying specialty-specific AI use cases
  • Aligning AI with workflows (pre-diagnosis, treatment, aftercare)
  • Pilot planning: timelines, data, feedback loops
  • Team roles: clinical champion, AI specialist, IT admin
  • Monitoring AI errors and root cause analysis
  • Change management in clinical teams
  • Example: Triage AI in the emergency room
  • Scaling AI solutions across the healthcare system
  • Evaluating impact and performance after implementation

Up to 100% funding for your continuing education

Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.

Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.