AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Medical treatment may impact patients differently based on their existing health conditions. In this third course, you’ll recommend treatments more suited to individual patients using data from randomized control trials. In the second week, you’ll apply machine learning interpretation methods to explain the decision-making of complex machine learning models. Finally, you’ll use natural language entity extraction and question-answering methods to automate the task of labeling medical datasets.
These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend that you take the Deep Learning Specialization.
Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Natural Language Processing, Machine Learning Methods, Medical Terminology, Machine Learning, Large Language Modeling, Medical Science and Research, AI Personalization, Treatment Planning, Deep Learning, Patient Treatment, Predictive Modeling, Feature Engineering, Precision Medicine, Clinical Trials, Health Informatics, Text Mining, Applied Machine Learning, Statistical Analysis
Reviews
4.7 (524 ratings)
5 stars
78.05%
4 stars
15.45%
3 stars
4%
2 stars
1.33%
1 star
1.14%
AS
Jun 8, 2020
Fantastic coursework teaching fundamentals required for analysis of medical domain data. Quality content with great assignments. Level of difficulty is intermediate for the assignments.
NA
Jun 7, 2020
Learned a lot about interpretations of both machine learning and deep learning models. Introduction to basic NLP techniques was a great start too. The overall course is really good.
From the lesson
ML Interpretation
In this week, you will learn how to interpret deep learning models, and also feature importance in machine learning.