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AL-504 (A) · AI in Health Care/Official Syllabus

AI in Health Care (AL-504 (A)) - Official Syllabus

1
Unit 1

Disease detection with computer vision

  • Medical Image Diagnosis
  • Eye Disease and Cancer Diagnosis
  • Building and Training a Model for Medical Diagnosis
  • Training, prediction, and loss
  • Image Classification and Class Imbalance
  • Generating More Samples
  • Model Testing
2
Unit 2

Evaluating models

  • Evaluating models Sensitivity, Specificity, and Evaluation Metrics
  • Accuracy in terms of conditional probability
  • Confusion matrix
  • ROC curve and Threshold
  • Image segmentation on MRI images Medical Image Segmentation
  • MRI Data and Image Registration
  • Segmentation, 2D U-Net and 3D U-Net
  • Data augmentation and loss function for segmentation
  • Different Populations and Diagnostic Technology
  • External validation
3
Unit 3

Linear prognostic models

  • Medical Prognosis
  • Atrial fibrillation
  • Liver Disease Mortality
  • Risk of heart disease
  • Evaluating Prognostic Models
  • Concordant Pairs
  • Risk Ties
  • Permissible Pairs
  • Prognosis with Tree-based models Decision trees for prognosis
  • fix overfitting
  • Different distributions
  • Missing Data example
  • Imputation
4
Unit 4

Survival Models and Time

  • Survival Model
  • Survival function
  • collecting time data
  • estimating the survival function
  • Build a risk model using linear and tree-based models Hazard Functions
  • Relative risk
  • Individual vs. baseline hazard
  • Survival Trees
  • Nelson Aalen estimator
5
Unit 5

Medical Treatment Effect Estimation

  • Analyze data from a randomized control trial
  • Average treatment effect
  • Conditional average treatment effect
  • T-Learner
  • S-Learner
  • C-for-benefit

Reference Books

  • ai-for-medical-diagnosis — Coursera Course — https://www.coursera.org/learn/ai-for-medical-diagnosis
  • ai-for-medical-prognosis — Coursera Course — https://www.coursera.org/learn/ai-for-medical-prognosis
  • ai-for-medical-treatment — Coursera Course — https://www.coursera.org/learn/ai-for-medical-treatment
  • Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again — Eric Topol — Basic Books — 1st edition 2019
  • Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes — Arjun Panesar — Apress — 1st ed. Edition, 2019
  • Artificial Intelligence in Healthcare — Elsevier Inc — 2020
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