BWH-CCDS Data Science Pathway Resource Website

An entry-level resource for Data Science in Radiology

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Project maintained by wfwiggins Hosted on GitHub Pages — Theme by mattgraham

List of Resources

Over time, we will put together a carefully curated list of resources with a mind for what is most useful and efficient for time-constrained residents. We will try to grade the accessibility of the content as "Novice", "Beginner", or "Intermediate".

Our definitions of experience
Novice	Limited or no prior coding experience
Beginner	Some prior coding experience, perhaps in another language (aside from Python) or unrelated to Data Science and Deep Learning
Intermediate	Basic familiarity with Python for Data Science and Deep Learning

Novice Resources

• Kaggle Intro to Python
• A 7-part introduction to the Python programming language, taught in the Kaggle Notebook self-contained programming environment.
• Kaggle 7-day Python Challenge
• A 7-day challenge for learning the basics of Python programming in the Kaggle Notebook (formerly known as "Kernel") self-contained programming environment.
• Python for Non-Programmers
• An extensive list of interactive tutorials and other online resources for learning the basics of programming in Python
• RadioGraphics - Deep Learning: A Primer for Radiologists
• Published in 2017, this general review of deep learning covers basic terminology and concepts with examples of applications to image analysis.
• Kaggle Notebook - Hello World for Deep Learning in Medical Imaging
• Self-guided tutorial for deep learning in medical imaging using Python
• No coding experience required
• Walkthrough of code training a model to differentiate chest and abdominal radiographs

Beginner Resources

• Python for Data Analysis by Wes McKinney (Amazon)
• Beginner level book covering basic topics in data science
• Employs common Python libraries: iPython, NumPy, Pandas and matplotlib
• Deep Learning with Python by Francois Chollet (Amazon)
• Beginner level book covering basic topics in deep learning and computer vision
• Written by the author of the Keras framework for TensorFlow - using Keras, now known as tf.keras
• The Missing Semester of Your CS Education - MIT
• A series of courses covering the basics of computing tools often used by programmers such as the command line interface (CLI or shell) and Git (version control).
• Python for Neuroimaging for Beginners by Kevin Cho
• Series of 4 YouTube videos covering basic Python functions for manipulating and processing image data.
• Geared toward neuroimaging, but skills are generalizable to all imaging subspecialties.

Intermediate Resources

• fast.ai Practical Deep Learning for Coders
• "Code first, theory later" series of tutorials in deep learning
• Covers computer vision, natural language processing and tabular learning
• Advanced course follows, delving deeper into fundamentals and theory of deep learning
• UC-Irvine CS190 Course: Deep Learning for Medical Imaging by Dr. Peter Chang (link to GitHub repository)
• Comprehensive introductory course with focus on medical imaging utilizing Python notebooks in Google Colab with the TensorFlow 2.0/Keras API.
• Links to tutorial videos and slides included in README.md file.
• Course notebooks can be downloaded from notebooks folder and uploaded to Google Colab.
• More to come...