Curated to help students engage in specialized learning of how AI is transforming medicine and the healthcare industry. Students get a chance to build real world, impactful group projects in the field of AI and medicine!

Deep Dive: AI + Medicine

Deep Dive: AI + Medicine

Our AI + Medicine Deep Dive is curated to help students engage in specialized learning of how AI is transforming medicine and the healthcare industry. Students get a chance to build real world, impactful projects in the field of AI and medicine!

Program Structure

Weeks 1 & 2:

Introduction to AI and medicine

Weeks 3 & 5:

Receive an introduction to key topics in AI and medicine - including medical data preparation, EDA, Convolutional Neural Networks, and more

Weeks 6 & 10:

Deep dive into some more complex topics which includes:

  • Image Segmentation

  • Regularization and Transfer Learning

  • Fundamentals of Clinical Evolution 

Program Structure

Weeks 1 to 2:

Introduction to AI and medicine

Weeks 3 to 5:

Receive an introduction to key topics in AI and medicine - including medical data preparation, EDA, Convolutional Neural Networks, and more

Weeks 6 to 10:

  • Image Segmentation

  • Regularization and Transfer Learning

  • Fundamentals of Clinical Evolution 

Deep dive into some more complex topics which includes:

Program Details

Illustration of a woman using a smartphone with a large screen displaying a pie chart, speech bubbles, and icons representing health data and a chatbot, surrounded by abstract leaves.

This program is conducted entirely online!

  • 25 hours over 10 weeks (weekends).

  • Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session).

  • Completion of AI Scholars or background in coding.

  • Grades 8-12.

  • A group project with 3-4 other students.

Here is the program brochure with more details!

An illustration of a woman interacting with a smartphone displaying a colorful pie chart, a chat bubble, a heart monitor icon, and a chatbot robot with a speech bubble, representing data analysis and digital communication.

Program Details

This program is conducted entirely online!

  • 25 hours over 10 weeks (weekends).

  • Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session).

  • Completion of AI Scholars or background in coding.

  • Grades 8-12.

  • A group project with 3-5 other students.

Here is the program brochure with more details!

AI DEEP DIVE AI MEDICAL SYLLABUS

Session 1
Session 2
Session 3
Session  4
Session 5
Session 6
Session 7
Session 8
Session 9
Session 10
Lecture 1: Theory
Intro to AI and Medicine
Medical data preparation and Exploratory Data Analysis (EDA)
Fundamentals of Neural Networks (regression)
Convolutional Neural Networks (classification)
Advanced Convolutional Neural Networks
Convolutional Neural Networks (segmentation)
Tools for Improving CNNs: Regularization and Transfer Learning
Fundamentals of Clinical Evaluation and other AI applications
Ethics in Clinical AI
Presentations
Lecture 2: Code Walk-Through
Intro to Python & Basic Programming
Basic Pipeline of Executing a Medical Data Science Project
Basic Introduction of Tensorflow Keras
Image classification task
Advanced image classification task
Image segmentation task
Image segmentation with transfer learning
Statistics and thorough evaluation pipelines
Project work
Presentations
Section:
Hands-on work
Hands-on work
Hands-on work
Hands-on work
Hands-on work
Project: Start Projects with EDA!
Project: Baseline Model (Template)
Project: Advanced Model (Upgrade from Baseline)
Project work
Closing Ceremony

DEEP DIVE AI + MEDICINE SYLLABUS

Lecture 1:

Theory

Intro to AI and Medicine

Session 1

Medical data preparation and Exploratory Data Analysis (EDA)

Session 2

Fundamentals of Neural Networks (regression)

Session 3

Convolutional Neural Networks (classification)

Session 4

Advanced Convolutional Neural Networks

Session 5

Convolutional Neural Networks (segmentation)

Session 6

Tools for Improving CNNs: Regularization and Transfer Learning

Session 7

Fundamentals of Clinical Evaluation and other AI applications

Session 8

Presentations

Session 10

Lecture 2:

Code Walk-Through

Intro to Python & Basic Programming

Basic Pipeline of Executing a Medical Data Science Project

Basic Introduction of Tensorflow Keras

Image classification task

Advanced image classification task

Image segmentation task

Image segmentation with transfer learning

Statistics and thorough evaluation pipelines

Section:

Hands-on work

Hands-on work

Hands-on work

Hands-on work

Hands-on work

Project: Start Projects with EDA!

Project: Baseline Model (Template)

Project: Advanced Model (Upgrade from Baseline)

Closing Ceremony

Ethics in Clinical AI

Session 9

Project work

Presentations

Project work