Deep Learning in Health Care and its Practical Limitations
Total time needed: ~1 hour
This Shortlist gives you a brief introduction to Deep Learning in HealthCare and its practical limitations on why deep learning is adopted in hospitals yet?
Potential Use Cases
How to reduce the gap between academic and production level code and how to ship products using Data Augmentation, Data Synthesis, Pre-Trained Models and how to engineer reliable deep learning systems?
Who is This For ?
INTERMEDIATE Data Scientist, Data Analyst, ML Engineer, ML Researchers, Software Engineer, etc
Click on each of the following annotated items to see details.
VIDEO 1. Deep Learning in HealthCare and Its Practical Limitations
Deep Learning has a lot of potential in Healthcare. But why don’t these techniques are adopted in hospitals yet? What are the gaps between academic research and production level code in Deep Learning and Healthcare? How can we mitigate this production level gap in Deep Learning and Healthcare, and what are some of the tools and techniques we can deploy?
ARTICLE 2. Why Is Building Machine Learning Products For Healthcare So Hard?
What Data is a Nightmare for Healthcare? What are the design challenges? Why Security, Compliance and Regulations slowed down innovation?
PAPER 3. CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness
How to use Data Augmentation to mitigate Small Data problem in Deep Learning?
PAPER 4. Unsupervised Histopathology Image Synthesis
How to use Data Synthesis to mitigate Small Data problem in Deep Learning?
PAPER 5. CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
How to use Pre-Trained Models like BERT to mitigate Small Data problem in Deep Learning?
PAPER 6. CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting
How to improve Robustness and Generalization of DL Algorithms?
PAPER 7. Developing a delivery science for artificial intelligence in healthcare
How to improve Safety and Regulations in HealthCare?
PAPER 8. Engineering Reliable Deep Learning Systems
Why DL Engineering? What are DL Engineering Lifecycle Activities? What are the current challenges in DL Engineering?