Foundations of mining non-structured medical data
- Offered byCoursera
Foundations of mining non-structured medical data at Coursera Overview
Duration | 7 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Foundations of mining non-structured medical data at Coursera Highlights
- Earn a shareable certificate upon completion.
- Flexible deadlines according to your schedule.
Foundations of mining non-structured medical data at Coursera Course details
- The goal of this course is to understand the foundations of Big Data and the data that is being generated in the health domain and how the use of technology would help to integrate and exploit all those data to extract meaningful information that can be later used in different sectors of the health domain from physicians to management, from patients to care givers, etc. The course will offer to the student a high-level perspective of the importance of the medical context within the European context, the types of data that are managed in the health (clinical) context, the challenges to be addressed in the mining of unstructured medical data (text and image) as well as the opportunities from the analytical point of view with an introduction to the basics of data analytics field.
Foundations of mining non-structured medical data at Coursera Curriculum
Introduction
Introduction
Big Data (I)
Big Data (II)
Importance of medical domain in the European cost context
Big Data in medical domain: opportunities and challenges
Data generated in the health domain
Introduction: evaluation test
Challenges in unstructured data in health domain
Challenges and problems in biomedical texts
Challenges and problems in medical images
Challenges in unstructured data in health: evaluation test
NLP in medical domain
Introduction to NLP pipeline and tasks
Tools and frameworks: general purpose
Tools and frameworks: medical domain
Vocabularies and ontologies (I)
Vocabularies and ontologies (II)
EHR analysis: structure, content and challenges
NLP in medical domain: evaluation test
Medical Image Analysis
Introduction of digital image basic concepts applied to medical image (I)
Introduction of digital image basic concepts applied to medical image (II)
Structuring image information
Case of use: Digital pathology. An example for breast cancer histological images
Medical image analysis: evaluation test
Data Analysis of structured information
Data mining problems and techniques
Data mining basics (I)
Data mining basics (II)
Classification (I)
Classification (II)
Clustering
Association
Validation
Data analysis: evaluation test
Foundations of mining non-structured medical data at Coursera Admission Process
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