Course Outline

Introduction to Multimodal AI for Healthcare

  • Overview of AI applications in medical diagnostics
  • Types of healthcare data: structured vs. unstructured
  • Challenges and ethical considerations in AI-driven healthcare

Medical Imaging and AI

  • Introduction to medical imaging formats (DICOM, PACS)
  • Deep learning for X-ray, MRI, and CT scan analysis
  • Case study: AI-assisted radiology for disease detection

Electronic Health Records (EHR) and AI

  • Processing and analyzing structured medical records
  • Natural Language Processing (NLP) for unstructured clinical notes
  • Predictive modeling for patient outcomes

Multimodal Integration for Diagnostics

  • Combining medical imaging, EHR, and genomic data
  • AI-driven decision support systems
  • Case study: Cancer diagnosis using multimodal AI

Speech and NLP Applications in Healthcare

  • Speech recognition for medical transcription
  • AI-powered chatbots for patient interaction
  • Clinical documentation automation

AI for Predictive Analytics in Healthcare

  • Early disease detection and risk assessment
  • Personalized treatment recommendations
  • Case study: AI-driven predictive models for chronic disease management

Deploying AI Models in Healthcare Systems

  • Data preprocessing and model training
  • Real-time AI implementation in hospitals
  • Challenges in deploying AI in medical environments

Regulatory and Ethical Considerations

  • AI compliance with healthcare regulations (HIPAA, GDPR)
  • Bias and fairness in medical AI models
  • Best practices for responsible AI deployment in healthcare

Future Trends in AI-Driven Healthcare

  • Advancements in multimodal AI for diagnostics
  • Emerging AI techniques for personalized medicine
  • The role of AI in the future of healthcare and telemedicine

Summary and Next Steps

Requirements

  • Understanding of AI and machine learning fundamentals
  • Basic knowledge of medical data formats (DICOM, EHR, HL7)
  • Experience with Python programming and deep learning frameworks

Audience

  • Healthcare professionals
  • Medical researchers
  • AI developers in the healthcare industry
 21 Hours

Delivery Options

Private Group Training

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    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from £5700 online delivery, based on a group of 2 delegates, £1800 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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