In this post, you will get a quick overview on free MIT course on machine learning for healthcare. This is going to be really helpful for machine learning / data science enthusiasts as building machine learning solutions to serve healthcare requirements comes with its own set of risks. It will be good to learn about different machine learning techniques, applications related disease progression modeling, cardiac imaging, pathology etc, risks and risk mitigation techniques.
Here is the link to the course – Machine Learning for Healthcare
Here are the links to some of the important course content:
The entire course material can be downloaded from this page – Download course materials of course – Machine Learning & Healthcare
Here are some key topics which has been covered as part of this course:
- Machine learning in healthcare
- Overview of clinical care
- Deep dive into clinical data
- Risk stratification
- Physiological time series
- NLP & healthcare
- Machine learning & cardiac imaging
- Machine learning for pathology
- Machine learning and mammography
- Causal inference
- Reinforcement learning
- Disease progression modelling
- Precision medicine
- Fairness (Ethical AI)
- Interpretability
- Healthcare regulations and AI / ML
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I found it very helpful. However the differences are not too understandable for me