AL-504-A AI in Health Care - Nov 2023 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aWhat are the applications of AI in health care? Illustrate how remote patient monitoring works by using AI.
   How to answer

   • Define AI in healthcare and list major application areas
   • Explain remote patient monitoring workflow with AI
   • Give examples of sensors, data transmission and alerts
   • Mention benefits like early detection and reduced hospitalization
2. 7 Marks
   bExplain the concept of wearable health technology and its connection to AI.
   How to answer

   • Define wearable health technology with examples
   • Explain types of data collected
   • Describe connection to AI for analysis and prediction
   • Mention benefits and challenges
3. 7 Marks
   aDescribe how AI is being employed in managing and optimizing hospital resources.
   How to answer

   • List hospital resources: beds, staff, equipment, scheduling
   • Explain AI for demand forecasting and allocation
   • Describe optimization for scheduling and inventory
   • Give examples of operational efficiency gains
4. 7 Marks
   bWhich evaluation metrics are used for evaluating the model's efficiency?
   How to answer

   • Define model efficiency evaluation need
   • List metrics: accuracy, precision, recall, F1, AUC-ROC
   • Explain relevance to medical models
   • Mention validation and clinical metrics
5. 7 Marks
   aDiscuss the concept of linear prognostic models for medical Prognosis.
   How to answer

   • Define linear prognostic models and prognosis
   • Explain linear relationship and coefficients
   • Discuss examples like Cox proportional hazards linear part
   • Mention uses and limitations in medical prognosis
6. 7 Marks
   bHow does AI assist in medical image segmentation?
   How to answer

   • Define medical image segmentation
   • Explain AI methods: CNN, U-Net
   • Describe steps: preprocessing, segmentation, post-processing
   • Mention clinical applications
7. 7 Marks
   aDifferentiate between the survival model and the time survival model.
   How to answer

   • Define survival model and time survival model
   • Compare on purpose, output and time component
   • Present differences in tabular form
   • Give clinical examples of each
8. 7 Marks
   bHow does the Nelson Aalen estimator estimate the cumulative hazard function?
   How to answer

   • Define cumulative hazard function and Nelson-Aalen estimator
   • Give formula summing d/N at event times
   • Explain steps using at-risk and event counts
   • Mention use in survival analysis
9. 7 Marks
   aWhat is the CATE (conditional average treatment effect) and why do we use it?
   How to answer

   • Define CATE as conditional average treatment effect
   • Explain conditioning on covariates vs ATE
   • Describe use in personalized medicine
   • Mention estimation methods
10. 7 Marks
    bHow does AI improve patient triage in emergency rooms?
    How to answer

    • Define patient triage in emergency rooms
    • Explain AI inputs: vitals, symptoms, history
    • Describe prioritization and risk stratification
    • Mention benefits: speed, accuracy, outcomes
11. 7 Marks
    aWhich techniques are used to fix overfitting?
    How to answer

    • Define overfitting in ML models
    • List techniques: regularization, dropout, cross-validation
    • Explain data augmentation and early stopping
    • Mention relevance to healthcare data
12. 7 Marks
    bHow does AI predict the risk of heart disease?
    How to answer

    • List risk factors and data sources: EHR, ECG, imaging
    • Explain ML models for heart disease prediction
    • Describe feature selection and validation
    • Mention early intervention benefits
13. 7 Marks
    aWhat do you understand by survival tree? Explain with an example.
    How to answer

    • Define survival tree and its nodes
    • Explain splitting based on survival differences
    • Provide example with patient groups
    • Mention interpretation for prognosis
14. 7 Marks
    bHow does AI contribute to improving the efficiency of Electronic Health Record (EHR) systems?
    How to answer

    • Define EHR systems and challenges
    • Explain AI for documentation, coding and retrieval
    • Describe clinical decision support and automation
    • Mention efficiency and error reduction
15. 14 Marks
    Write short notes on any two:

    1. a)AI in Disease Detection
    2. b)Virtual Health Assistants
    3. c)Medication Adherence
    4. d)Sentiment Analysis
    How to answer

    • Select any two topics from the four options
    • Define each with key AI techniques
    • Give healthcare examples and benefits
    • Conclude with impact and challenges