AI for Medicine Specialization

This repository contains my assignment solutions to the AI for Medicine Specialization course from coursera. This repo is for my personal reference. Try to do the assignments by your own. Use these as a reference material if you are stuck in the assignments.

• Course link - https://www.coursera.org/specializations/ai-for-medicine

AI for Medical Diagnosis

• Week 1

  • Ungraded Lab
    • Counting labels and weighted loss function
    • Data Exploration & Image Pre-Processing
    • Densenet
    • Patient Overlap - practice
  • Chest X-Ray Medical Diagnosis with Deep Learning | Pdf Version

• Week 2

  • Evaluation of Diagnostic Models | Pdf Version

• Week 3

  • Ungraded Lab
    • Explore MRI data
    • Get a sub section
    • Implement U-Net
  • Brain Tumor Auto-Segmentation for Magnetic Resonance Imaging (MRI) | Pdf Version

AI for Medical Prognosis

• Week 1

  • Ungraded Lab
    • Combine Features
    • Concordance Index
    • Create a Linear Model
    • Risk Scores, Pandas and Numpy
  • Build and Evaluate a Linear Risk Model | Pdf Version

• Week 2

  • Ungraded Lab
    • Missing Values, Decesion Tree Classifier, Mask, Imputation
  • Risk Models Using Tree-based Models | Pfd Version

• Week 3

  • Ungraded Lab
    • Count Patients, Kaplan-Meier
  • Survival Estimates that Vary with Time | Pdf Version

• Week 4

  • Ungraded Lab
    • One-hot encode, Categorical variables, Hazard function, Permissible pairs with censoring and time
  • Cox Proportional Hazards and Random Survival Forests | Pdf Version

AI for Medical Treatment

• Week 1

  • Ungraded Lab
    • Logistic Regression Model Interpretation
    • Model TrainingTuning Basics with Sklearn
    • Pandas for a Medical Dataset
  • Estimating Treatment Effect Using Machine Learning | Pdf Version

• Week 2

  • Cleaning Text
  • Preparing Input for Text Classification
  • Using BioC format and the NegBio Library
  • Natural Language Entity Extraction | Pdf Version

• Week 3

  • Ungraded Lab
    • Permutation Method
    • Introduction To GradCAM (Part 1)
    • GradCAM Continuation (Part 2)
  • Model Interpretation Methods | Pdf Version

Certificate