[major=AI | course_id=AIM301m | syllabus_id=11175 | semester=7 | combo=AI17_COM3 | title=AI for Medicine]
Course ID: AIM301m
Title EN: AI for Medicine
Title VI: Ứng dụng TTNT cho y học
Credits: 3.0
Prerequisites: PFP191
Description: Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. The aim of this unit is to introducethe current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. Students will be guided to analyze data on patient, such as diseases, medications, tests, or valuable health information, and get a sense of how AI could transform patient care and diagnoses.
Student tasks: - Students must attend at least 80% of contact slots in order to be accepted to the final examination.
- Student is responsible to do all exercises, assignments and labs given by instructor in class or at home and submit on time
- Use laptop in class only for learning purpose
- Promptly access to the FU FLM at https://flm.fpt.edu.vn/ for up-to-date course information
Tools: No
Course type: coursera_hybrid
Decision: 358/QĐ-ĐHFPT dated 04/03/2024
Approved date: 2024-04-03
CLO1: Pre-process data and set up a pre-trained neural network.
[1] category=Assignment 1; type=on-going; weight=5.0; duration=60'; question_type=CLO1; grading_guide=algorithms and labs 1-4; completion_criteria=; clos=>0
[2] category=Assignment 2; type=on-going; weight=5.0; duration=60'; question_type=CLO2, CLO3; grading_guide=algorithms and labs 5-8; completion_criteria=; clos=>0
[3] category=Assignment 3; type=on-going; weight=5.0; duration=60'; question_type=CLO4, CLO5; grading_guide=algorithms and labs 9-15; completion_criteria=; clos=>0
[4] category=Assignment 4; type=on-going; weight=5.0; duration=60'; question_type=CLO6; grading_guide=algorithms and labs 16-20; completion_criteria=; clos=>0
[5] category=Assignment 5; type=on-going; weight=5.0; duration=60'; question_type=CLO7; grading_guide=algorithms and labs 21-23; completion_criteria=; clos=>0
[6] category=Assignment 6; type=on-going; weight=5.0; duration=60'; question_type=CLO8 - CLO9; grading_guide=algorithms and labs 24-26; completion_criteria=; clos=>0
[7] category=Progress test 1; type=on-going; weight=10.0; duration=20'-30'; question_type=CLO1, CLO2, CLO3; grading_guide=concepts (AI for medical diagnosis), slides 1.1-1.3; completion_criteria=; clos=>0
[8] category=Progress test 2; type=on-going; weight=10.0; duration=20'-30'; question_type=CLO4, CLO5, CLO6; grading_guide=concepts (AI for medical prognosis), slides 2.1-2.4; completion_criteria=; clos=>0
[9] category=Progress test 3; type=on-going; weight=10.0; duration=20'-30'; question_type=CLO7, CLO8, CLO9; grading_guide=concepts (AI for medical treatment), slides 3.1-3.3; completion_criteria=; clos=>0
[10] category=Final exam; type=Final exam; weight=40.0; duration=60'; question_type=CLO1 - CLO9; grading_guide=concepts, algorithms;
all studied slides and labs; completion_criteria=; clos=4
[1] desc=Spec: AI for Medicine Specialization; author=Coursera; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/specializations/ai-for-medicine#courses
[2] desc=MOOC 1: AI for Medical Diagnosis; author=Coursera; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/ai-for-medical-diagnosis?specialization=ai-for-medicine
[3] desc=MOOC 2: AI for Medical Prognosis; author=Coursera; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/ai-for-medical-prognosis?specialization=ai-for-medicine
[4] desc=MOOC 3: AI For Medical Treatment; author=Coursera; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/ai-for-medical-treatment?specialization=ai-for-medicine
[5] desc=Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems; author=Aurélien Géron; publisher=O'Reilly Media; edition=1st edition; isbn=978-1491962299; main=; online=True; note=http://ds.libol.fpt.edu.vn/
[6] desc=Healthcare IT Support Specialization; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/specializations/healthcare-it
[7] desc=AI For Everyone; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/learn/ai-for-everyone
Session 1: Course introduction:
- Introduce the materials of the courses and how to asses these materials
- Introduce the assignments and how to pass
- Introduce the way to log on the system to submit the assignments and class forum with enroll key.
Topic: Offline; Teaching type: CLO1; LO: IT
ITU: Course Implementation
- Syllabus AIM301m
- Slides, Videos
Materials: mat1
Download: Read Slide and and Seft-Review

Session 2: 1. AI for Medical Diagnosis
1.1. Disease Detection with Computer Vision
Applications of Computer Vision to Medical Diagnosis
Handling Class Imbalance and Small Training Sets
Checking your Model Performance
Topic: Offline; Teaching type: CLO1; LO: T
ITU: Slides, Videos of Disease Detection with Computer Vision
Download: Read Slide and and Seft-Review

Session 3: Lab 1 - Data Exploration & Image Pre-Processing
Topic: Offline; Teaching type: CLO1; LO: T
ITU: Slides, Videos of Disease Detection with Computer Vision, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 4: Lab 2 - Counting labels and weighted loss function
Topic: Offline; Teaching type: CLO1; LO: T
ITU: Slides, Videos of Disease Detection with Computer Vision, Lab Tutorial
Download: Read Lab and and Seft-Review
CLO2: Evaluate models by accuracy, specificity, predictive value, confidence intervals, ROC curve, and F1 score.
Session 1: Lab 3 - Densenet
Topic: Offline; Teaching type: CLO1; LO: T
ITU: Slides, Videos of Disease Detection with Computer Vision, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Lab 4 - Patient Overlap - Practice
Topic: Offline; Teaching type: CLO1; LO: T
ITU: Slides, Videos of Disease Detection with Computer Vision, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Assignment 1: Chest X-Ray Medical Diagnosis with Deep Learning
Topic: Offline; Teaching type: CLO1; LO: U
ITU: Assignmet 1
Download: Assignmet 1

Session 4: Review Assignment 1
Topic: Offline; Teaching type: CLO1; LO: U
ITU: Assignmet 1
Download: Assignmet 1
CLO3: Diagnose diseases from x-rays and 3D MRI brain images.
Session 1: 1. AI for Medical Diagnosis
1.2. Evaluating Models
Key Evaluation Metrics
Threshold and Evaluation Metrics
Interpreting Confidence Intervals Correctly
Topic: Offline; Teaching type: CLO2; LO: T
ITU: Slides, Videos of Evaluating Models
Download: Read Slide and and Seft-Review

Session 2: Lab 5 - ROC Curve and Threshold
Topic: Offline; Teaching type: CLO2; LO: T
ITU: Slides, Videos of Evaluating Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: 1. AI for Medical Diagnosis
1.3. Image Segmentation on MRI Images
Exploring MRI Data
Image Segmentation
Practical Considerations
Topic: Offline; Teaching type: CLO3; LO: T
ITU: Slides, Videos of Image Segmentation on MRI Images
Download: Read Slide and and Seft-Review

Session 4: Lab 6 - Explore MRI data
Topic: Offline; Teaching type: CLO3; LO: T
ITU: Slides, Videos of Image Segmentation on MRI Images, Lab Tutorial
Download: Read Lab and and Seft-Review
CLO4: Walk through examples of prognostic tasks.
Session 1: Lab 7 - Get a sub section
Topic: Offline; Teaching type: CLO3; LO: T
ITU: Slides, Videos of Image Segmentation on MRI Images, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Lab 8 - Implement U-Net
Topic: Offline; Teaching type: CLO3; LO: T
ITU: Slides, Videos of Image Segmentation on MRI Images, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Assignment 2: Brain Tumor Auto-Segmentation for Magnetic Resonance Imaging (MRI)
Topic: Offline; Teaching type: CLO2 - CLO3; LO: U
ITU: Assignment 2
Download: Assignment 2

Session 4: Review Assignment 2
Topic: Offline; Teaching type: CLO2 - CLO3; LO: U
ITU: Assignment 2
Download: Assignment 2
CLO5: Predict patient survival rates more accurately using tree-based models.
Session 1: Summary AI for Medical Diagnosis
Topic: Offline; Teaching type: CLO1 - CLO3; LO: T
ITU: Slides, Videos of AI for Medical Diagnosis, Labs
Download: Read Slide and and Seft-Review

Session 2: Progress Test 1
Topic: Offline; Teaching type: CLO1 - CLO3; LO: U
ITU: Progress Test 1
Download: Progress Test 1

Session 3: Review Progress Test 1
Topic: Offline; Teaching type: CLO1 - CLO3; LO: U
ITU: Progress Test 1
Download: Progress Test 1

Session 4: 2. AI for Medical Prognosis
2.1. Linear Prognostic Models
What is the Risk of Getting a Disease?
Prognostic Models in Medical Practice
Representing Feature Interactions
Evaluating Prognostic Models
Topic: Offline; Teaching type: CLO4; LO: T
ITU: Slides, Videos of Linear Prognostic Models
Download: Read Slide and and Seft-Review
CLO6: Navigate practical challenges in medicine, like missing data.
Session 1: Lab 9 - Create a linear model
Topic: Offline; Teaching type: CLO4; LO: T
ITU: Slides, Videos of Linear Prognostic Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Lab 10 - Risk Scores, Pandas and Numpy
Topic: Offline; Teaching type: CLO4; LO: T
ITU: Slides, Videos of Linear Prognostic Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Lab 11 - Combine Features
Topic: Offline; Teaching type: CLO4; LO: T
ITU: Slides, Videos of Linear Prognostic Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 4: Lab 12 - Concordance index
Topic: Offline; Teaching type: CLO4; LO: T
ITU: Slides, Videos of Linear Prognostic Models, Lab Tutorial
Download: Read Lab and and Seft-Review
CLO7: Estimate treatment effects on patients using data from randomized trials.
Session 1: 2. AI for Medical Prognosis
2.2. Prognosis with Tree-based Models
Tree-based Models
Identifying Missing Data
Using Imputation to Handle Missing Data
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Prognosis with Tree-based Models
Download: Read Slide and and Seft-Review

Session 2: Lab 13 - Decision trees
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Prognosis with Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Lab 14 - Missing data and applying a mask
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Prognosis with Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 4: Lab 15 - Imputation
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Prognosis with Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review
CLO8: Explore methods to interpret diagnostic and prognostic models.
Session 1: Assignment 3: Risk Models Using Tree-based Models
Topic: Offline; Teaching type: CLO5 - CLO6; LO: U
ITU: Assignment 3
Download: Assignment 3

Session 2: Review Assignment 3
Topic: Offline; Teaching type: CLO5 - CLO6; LO: U
ITU: Assignment 3
Download: Assignment 3

Session 3: 2. AI for Medical Prognosis
2.3. Survival Models and Time
Survival Estimates
Time to Event Data
Estimate Survival with Censored Data
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Survival Models and Time
Download: Read Slide and and Seft-Review

Session 4: Lab 16 - Counting patients
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Survival Models and Time, Lab Tutorial
Download: Read Lab and and Seft-Review
CLO9: Automate the task of labeling medical datasets using natural language processing.
Session 1: Lab 17 - Kaplan Meier
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Survival Models and Time, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: 2. AI for Medical Prognosis
2.4. Build a Risk Model Using Linear and Tree-based Models
Survival and Hazard Functions
Customizing Risk Models to Individual Patients
Non-linear Risk Models with Survival Trees
Evaluate Survival Models
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Build a Risk Model Using Linear and Tree-based Models
Download: Read Slide and and Seft-Review

Session 3: Lab 18 - Categorical variables
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Build a Risk Model Using Linear and Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 4: Lab 19 - Hazard function
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Build a Risk Model Using Linear and Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review
Session 1: Lab 20 - Permissible pairs
Topic: Offline; Teaching type: CLO5 - CLO6; LO: T
ITU: Slides, Videos of Build a Risk Model Using Linear and Tree-based Models, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Assignment 4: Cox proportional hazards and random survival forests
Topic: Offline; Teaching type: CLO5 - CLO6; LO: U
ITU: Assignment 4
Download: Assignment 4

Session 3: Review Assignment 4
Topic: Offline; Teaching type: CLO5 - CLO6; LO: U
ITU: Assignment 4
Download: Assignment 4

Session 4: Summary AI for Medical Prognosis
Topic: Offline; Teaching type: CLO4 - CLO6; LO: T
ITU: Slides, Videos of AI for Medical Prognosis, Labs
Download: Read Slides and and Seft-Review
Session 1: Progress Test 2
Topic: Offline; Teaching type: CLO4 - CLO6; LO: U
ITU: Progress Test 2
Download: Progress Test 2

Session 2: Review Progress Test 2
Topic: Offline; Teaching type: CLO4 - CLO6; LO: U
ITU: Progress Test 2
Download: Progress Test 2

Session 3: 3. AI For Medical Treatment
3.1. Treatment Effect Estimation
Introduction
Randomized Control Trials
Average Treatment Effect
Individualized Treatment Effect
Topic: Offline; Teaching type: CLO7; LO: T
ITU: Slides, Videos of Treatment Effect Estimation
Download: Read Slide and and Seft-Review

Session 4: Lab 21 - Pandas operations on Medical Data
Topic: Offline; Teaching type: CLO7; LO: T
ITU: Slides, Videos of Treatment Effect Estimation, Lab Tutorial
Download: Read Lab and and Seft-Review
Session 1: Lab 22 - Model Training Tuning Basics with Sklearn
Topic: Offline; Teaching type: CLO7; LO: T
ITU: Slides, Videos of Treatment Effect Estimation, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Lab 23 - Logistic Regression Model Interpretation
Topic: Offline; Teaching type: CLO7; LO: T
ITU: Slides, Videos of Treatment Effect Estimation, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Assignment 5: Treatment Effect Estimation
Topic: Offline; Teaching type: CLO7; LO: U
ITU: Assignment 5
Download: Assignment 5

Session 4: Review Assignment 5
Topic: Offline; Teaching type: CLO7; LO: U
ITU: Assignment 5
Download: Assignment 5
Session 1: 3. AI For Medical Treatment
3.2. Medical Question Answering
Question Answering
Automatic Labeling
Evaluate Automatic Labeling
Topic: Offline; Teaching type: CLO8; LO: T
ITU: Slides, Videos of Medical Question Answering
Download: Read Slide and and Seft-Review

Session 2: Lab 24 - Cleaning Text
Topic: Offline; Teaching type: CLO8; LO: T
ITU: Slides, Videos of Medical Question Answering, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 3: Lab 25 - BioC format and the NegBio Library
Topic: Offline; Teaching type: CLO8; LO: T
ITU: Slides, Videos of Medical Question Answering, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 4: Lab 26 - Preparing Input for Text Classification
Topic: Offline; Teaching type: CLO8; LO: T
ITU: Slides, Videos of Medical Question Answering, Lab Tutorial
Download: Read Lab and and Seft-Review
Session 1: Assignment 6: Natural Language Entity Extraction
Topic: Offline; Teaching type: CLO8; LO: U
ITU: Assignment 6
Download: Assignment 6

Session 2: Review Assignment 6
Topic: Offline; Teaching type: CLO8; LO: U
ITU: Assignment 6
Download: Assignment 6

Session 3: 3. AI For Medical Treatment
3.3. ML Interpretation
Feature Importance
Individual Feature Importance
Interpreting Deep Learning Models
Topic: Offline; Teaching type: CLO9; LO: T
ITU: Slides, Videos of ML Interpretation
Download: Read Slide and and Seft-Review

Session 4: Lab 27 - Permutation method
Topic: Offline; Teaching type: CLO9; LO: T
ITU: Slides, Videos of ML Interpretation, Lab Tutorial
Download: Read Lab and and Seft-Review
Session 1: Lab 28 - GradCam Part 1 & 2
Topic: Offline; Teaching type: CLO9; LO: T
ITU: Slides, Videos of ML Interpretation, Lab Tutorial
Download: Read Lab and and Seft-Review

Session 2: Summary AI For Medical Treatment
Topic: Offline; Teaching type: CLO7 - CLO9; LO: T
ITU: Slides, Videos of AI For Medical Treatment, Labs
Download: Read Slide and and Seft-Review

Session 3: Progress Test 3
Topic: Offline; Teaching type: CLO7 - CLO9; LO: U
ITU: Progress Test 3
Download: Progress Test 3

Session 4: Review Progress Test 3
Topic: Offline; Teaching type: CLO7 - CLO9; LO: U
ITU: Progress Test 3
Download: Progress Test 3