AI-for-Medicine_3_Treatment This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Treatment" from DeepLearning.AI Coursera. Enjoy!
Week
Module
Gist
1-1
Intro
Intro Course
1-2
Randomized
Absolute Risk Reduction Randomized Control Trials Pandas for a Medical Dataset
1-3
Average Treatment Effect
Clarifications about Upcoming Causal Inference Causal Inference Average Treatment Effect Conditional Average Treatment Effect T-Learner S-Learner Model Training/Tuning Basics with Sklearn
1-4
Individualized treatment effect
Evaluate Individualized Treatment Effect C-for-benefit C-for-benefit Calculation Logistic Regression Model Interpretation
Q
Measure Treatment Effects
_
A
Estimate Treatment Effect Using ML
^_^
2-1
Question answering
Words with Multiple MeaningsDefine the Answer in a Text Cleaning Text
2-2
Automatic labeling
Automatic Label Extraction for Medical Imaging Synonyms for Labels Is-a Relationships for Labels Presence or Absence of a Disease BioC Format and the NegBio Library
2-3
Ecaluate automatic labeling
Evaluating Label Extraction Precision, Recall and F1 Score Evaluating on Multiple Disease Categories Preparing Input for Text Classification
Q
Information Extraction with NLP
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A
Natural Language Entity Extraction
^_^
3-1
Feature importance
Drop Column Method Permutation Method Lab-Permutation
3-2
Individual Feature Importance
Chapley Values Combining Importances Shapley Values for all Patients
3-3
Interpret DL Models
Interpreting CNN Models Introduction to GradCAM (Part 1) Localization Maps Heat Maps GradCAM: Continuation (Part 2)
Q
ML Interpretation
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A
ML Interpretation
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