Healthcare Informatics Assignment: Discuss An AI Application For Medical Imaging

Published: 29 May, 2025
Category Assignment Subject Science
University ___ Module Title Healthcare Informatics
Count Words: 1500 words
Academic year: 2025

Learning Outcomes: Discuss An AI Application For Medical Imaging

  • Understand clinic use
  • Know dataset quality and diversity
  • Explore performance metrics
  • Know validation strategies
  • Find clinic evaluation
  • Apply ethical and regulatory requirements
  • Deploy an application in the real world

Requirements

  • Each student will select one AI application for medical imaging
  • Evaluate and summarize the application based on the 7 key points in the previous slide
  • If the information of a key point is not available yet, you should discuss how it can be done with references to relevant AI applications.
  • Word limit: max 1500 words; figures, graphs, tables, illustrations, in-text citations, references, etc. are not counted for the limit; penalty applies if exceeding the limit

Requirements

  • uAI recommended – demo access is provided
  • Other AI applications acceptable
  • Address the 7 key points given in the guidelines
  • Rephrase essential concepts to show your understanding, e.g. performance metrics
  • Use section titles as recommended: The scope of application, Training datasets, Performance metrics, validations, Clinical evaluation outcome, Ethical and regulatory, Deployment and improvement, Reference

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1. The Scope Of Application

  • Imaging modality, e.g. CT, MRI, X-ray, Angio etc.
  • Patient population, pediatric vs adult, inpatient vs outpatient etc.
  • Use conditions: e.g. lesion detection, scoliosis analysis, bone age assessment, fractures, pneumonia, PE, ICH, etc.

Healthcare Informatics Assignment

2. Dataset Quality And Diversity

  • Number of image, age-range, race-range, to represent the target population
  • Annotation quality, e.g. ground truth was established by experts (radiologists)
  • Bias assessment, e.g. demographic variation, equipment differences

3. Performance Metrics

Healthcare Informatics Assignment

4. Validation Strategy

  • Internal validation: the same dataset was used for the training and validation
  • External validation: the training dataset is different from the validation dataset, e.g. from different institutions or populations
  • Cross-validation: the dataset was split into multiple parts and training was done multiple times

Healthcare Informatics Assignment

5. Clinical Evaluation

  • Expert studies: AI performance vs the experts (radiologists)
  • Workflow integration: Evaluate how AI fits the clinical workflows
  • Decision support: Assess and quantify what AI improves/brings to the clinical practices, e.g., reduce workload, improve workflow, provide better confidence, etc.

Healthcare Informatics Assignment

6. Regulatory And Ethical Considerations

  • Compliance: HAS (Singapore), FDA (USA), NMPA (China) CE Mark (European), Number of image, age-range, race-range, to represent the target population
  • Transparency: How are the AI decisions understood?
  • Data privacy: compliance with PDDA, HIPPA, GDPR, PIPL, etc

7. Real-World Deployment

  • Pilot studies: deploy the application in a limited clinical setting
  • Monitoring: Track performance over time and across different settings
  • Feedback loop: Incorporate clinician feedback for continuous improvements

Healthcare Informatics Assignment

8. References

Mendeley 

  • APA 7th Edition
  • In-text citations whenever appropriate to avoid plagiarism
  • A list of references at the end
  • The words of references and in-text citations are excluded from the word limit
  • Recommendation: Use Mendeley reference manager or Endnote to help you manage references; Mendeley reference manager is free.

Grading Rubric – Healthcare Informatic Assignment

Healthcare Informatics Assignment

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