README - Literature & Resources¶
- This Literature & Resources subfolder is organized by subcategories (programmatically created from a
Zoterolibrary). - The aim is to collect relevant research papers and resources along with links and short descriptions about their relevance.
Limitations¶
- The literature subcategories are inspired by the those of
Papers with Code, see here. - Please note that they are neither collectively exhaustive, nor necessarily mutually disjoint and that I might adjust them over time.
- Since I am just starting out, many subfolders are still empty or even missing completely. I'll add more categories and content over time!
Table of Contents¶
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- A novel deep learning based framework for the detection and classification of breast cancer using transfer learning (July 1, 2019)
📖 - The benefits and harms of breast cancer screening: an independent review (2013-06)
📖 - European guidelines for quality assurance in breast cancer screening and diagnosis (2013)
📖 - Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art (June 9, 2020)
📖 - Artificial Intelligence: A Primer for Breast Imaging Radiologists (August 10, 2020)
📖 - Breast cancer incidence and mortality before and after implementation of the German mammography screening program (2020-08-01)
📖 - Deep learning in breast radiology: current progress and future directions (2021-01-15)
📖 - Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening (2019-03-19)
📖 - International evaluation of an AI system for breast cancer screening (2020)
📖 - nyukat/breast_cancer_classifier
💻 - Papers with Code - Breast Cancer Detection
📖 - Bibliography
- A novel deep learning based framework for the detection and classification of breast cancer using transfer learning (July 1, 2019)
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Courses, Specializations and Workshops
- AI for Medicine (offered by deeplearning.ai via Coursera)
📖 - Evaluations of AI Applications in Healthcare (offered by Stanford via Coursera)
📖 - AI in Healthcare Capstone (offered by Stanford via Coursera)
📖 - Introduction to Clinical Data (offered by Stanford via Coursera)
📖 - Fundamentals of Machine Learning for Healthcare (offered by Stanford via Coursera)
📖 - AI in Healthcare Specialization (offered by Stanford via Coursera)
📖 - Introduction to Healthcare (offered by Stanford via Coursera)
📖 - Machine Learning for Healthcare (MIT 6.S897/HST.S53)
📖 - Learn to Utilize AI in Healthcare (Udacity)
📖 - Bibliography
- AI for Medicine (offered by deeplearning.ai via Coursera)