Information Extraction from Free Text Data in Health from Coursera

In this MOOC, you will be introduced to advanced machine learning and natural language

processing techniques to parse and extract information from unstructured text documents in

healthcare, such as clinical notes, radiology reports, and discharge summaries. Whether you are an aspiring data scientist or an early or mid-career professional in data science or information technology in healthcare, it is critical that you keep up-to-date your skills in information extraction and analysis.

To be successful in this course, you should build on the concepts learned through other intermediate-level MOOC courses and specializations in Data Science offered by the University of Michigan, so you will be able to delve deeper into challenges in recognizing medical entities in health-related documents, extracting clinical information, addressing ambiguity and polysemy to tag them with correct concept types, and develop tools and techniques to analyze new genres of health information.

By the end of this course, you will be able to:

Identify text mining approaches needed to identify and extract different kinds of information from health-related text data

Create an end-to-end NLP pipeline to extract medical concepts from clinical free text using one terminology resource

Differentiate how training deep learning models differ from training traditional machine learning models

Configure a deep neural network model to detect adverse events from drug reviews

List the pros and cons of Deep Learning approaches."

What's inside

Syllabus

Week 1 | What is Information Extraction?

Welcome to Week 1! We start this week by getting familiar with the process of information extraction. We will see specific techniques, such as regular expressions to extract information. We will also cover several evaluation approaches for information extraction. Let's get started!

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Suitable for healthcare practitioners and computer scientists

Taught by esteemed instructors in machine learning and natural language processing

Offers a practical approach to information extraction in healthcare

Covers advanced deep learning models for detecting adverse events from drug reviews

Builds on concepts from intermediate-level courses in Data Science

Reviews summary

Specialized information extraction for healthcare

According to learners, this course offers a highly specialized deep dive into information extraction from free text data in health, specifically targeting professionals in healthcare data science. Students find the hands-on exercises and focus on real-world medical data to be particularly valuable and directly applicable to their work. The instructor's explanations are often clear and concise, covering topics like Named Entity Recognition (NER) and sequential classification effectively. However, a recurring warning is that the prerequisites are critical; learners emphasize the need for a strong background in ML and advanced NLP to succeed. Some also note that the deep learning section can be brief or feel high-level without enough practical depth.

Well-structured, building complexity week by week.

"The structure of the course was logical, building complexity week by week."

"The course delivered on its promise to introduce advanced methods for health text."

"The content on medical terminology resources was eye-opening."

Clear explanations and valuable insights from the instructor.

"The instructor's explanations were clear and concise."

"I appreciated the practical application insights provided by the instructor."

"The instructor was knowledgeable and explained concepts clearly."

Highly relevant, hands-on application to clinical data.

"The hands-on exercises involving clinical notes were particularly insightful and directly applicable to my work."

"It covers fundamental concepts well, and the focus on real-world medical data is invaluable."

"This course really helped me apply my existing ML skills to a new domain. I learned so much about handling unstructured clinical text."

Generally relevant, though some content might need updating.

"I found the content up-to-date and very relevant to current industry needs."

"I felt the course could use an update as some discussions felt a little behind the curve."

"I encountered a few broken links in the resources and the forum discussions were not very active."

Coverage of deep learning is often too brief or high-level.

"I found the deep learning section a bit brief, but it provided enough to get started."

"I found the introduction to deep learning quite superficial."

"I was disappointed with the lack of detailed coding examples and expected more hands-on coding tutorials for advanced techniques."

Requires strong background in ML and advanced NLP.

"Make sure you have a strong NLP background. The prerequisites were understated."

"Completely out of my depth. The course assumes too much prior knowledge. As someone new to NLP, this was not helpful at all."

"I struggled with the pace in Weeks 3 and 4. This course is not for beginners."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Information Extraction from Free Text Data in Health with these activities:

Review Python Basics

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Ensure a solid Python foundation

Browse courses on Python

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Review Python syntax
Practice writing Python code

Review 'Natural Language Processing with Python 2nd Edition'

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Review the fundamentals of NLP

View Natural Language Processing with Python:... on Amazon

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Read the first four chapters
Try out the exercises
Create a small NLP project

Join a NLP Study Group

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Collaborate and learn from peers

Browse courses on Natural Language Processing

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Find or start a study group
Discuss course concepts
Work on projects together

Six other activities

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Learn NLP with NLTK

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Enhance your NLP skills using NLTK

Browse courses on Natural Language Processing

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Complete the NLTK tutorial
Build a project using NLTK

Practice NLP with Kaggle

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Apply NLP using real-world Kaggle datasets

Browse courses on Natural Language Processing

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Find a relevant Kaggle competition
Explore the dataset
Build and train a model
Submit your results

Build a Named Entity Recognition Model

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Develop a practical understanding of NER

Browse courses on Named Entity Recognition

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Choose a dataset
Preprocess the data
Train and evaluate a model
Deploy the model

Write a Blog Post on NLP Concepts

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Demonstrate understanding by explaining NLP concepts

Browse courses on Natural Language Processing

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Choose a topic
Research and write the content
Publish and promote the blog post

Create a Course Summary

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Consolidate course materials for easy reference

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Gather notes, assignments, and resources
Organize and summarize the content
Create a digital or physical summary

Attend an NLP Conference or Workshop

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Immerse in the latest NLP research and applications

Browse courses on Natural Language Processing

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Find a relevant conference or workshop
Register and attend

Career center

Learners who complete Information Extraction from Free Text Data in Health will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Scientist

A Natural Language Processing Scientist uses Natural Language Processing techniques to build machine learning models that understand and generate text. These models can be used for a variety of applications, such as search engines, social media filters, and medical diagnosis. This course provides a strong foundation in the principles and techniques of NLP, and would be particularly useful for someone who wants to work as a Natural Language Processing Scientist in the healthcare industry.

See salaries and explore the career path for Natural Language Processing Scientist

Medical Data Analyst

A Medical Data Analyst collects, analyzes, and interprets medical data to improve patient care and outcomes. This data can come from a variety of sources, such as electronic health records, claims data, and patient surveys. This course provides a strong foundation in the principles and techniques of data analysis, and would be particularly useful for someone who wants to work as a Medical Data Analyst in the healthcare industry.

See salaries and explore the career path for Medical Data Analyst

Healthcare Data Scientist

A Healthcare Data Scientist uses data science techniques to improve patient care and outcomes. This data can come from a variety of sources, such as electronic health records, claims data, and patient surveys. This course provides a strong foundation in the principles and techniques of data science, and would be particularly useful for someone who wants to work as a Healthcare Data Scientist in the healthcare industry.

See salaries and explore the career path for Healthcare Data Scientist

Health Informatics Specialist

A Health Informatics Specialist uses informatics techniques to improve patient care and outcomes. This data can come from a variety of sources, such as electronic health records, claims data, and patient surveys. This course provides a strong foundation in the principles and techniques of health informatics, and would be particularly useful for someone who wants to work as a Health Informatics Specialist in the healthcare industry.

See salaries and explore the career path for Health Informatics Specialist

Clinical Data Analyst

A Clinical Data Analyst collects, analyzes, and interprets clinical data to improve patient care and outcomes. This data can come from a variety of sources, such as electronic health records, claims data, and patient surveys. This course provides a strong foundation in the principles and techniques of clinical data analysis, and would be particularly useful for someone who wants to work as a Clinical Data Analyst in the healthcare industry.

See salaries and explore the career path for Clinical Data Analyst

Data Engineer

A Data Engineer designs, builds, and maintains data pipelines that collect, store, and process data. This data can come from a variety of sources, such as sensors, databases, and social media. This course provides a strong foundation in the principles and techniques of data engineering, and would be particularly useful for someone who wants to work as a Data Engineer in the healthcare industry.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer builds and maintains machine learning models that can learn from data and make predictions. These models can be used for a variety of applications, such as fraud detection, spam filtering, and medical diagnosis. This course provides a strong foundation in the principles and techniques of machine learning, and would be particularly useful for someone who wants to work as a Machine Learning Engineer in the healthcare industry.

See salaries and explore the career path for Machine Learning Engineer

Information Architect

An Information Architect designs and builds information systems that are easy to use and understand. These systems can include websites, databases, and software applications. This course provides a strong foundation in the principles and techniques of information architecture, and would be particularly useful for someone who wants to work as an Information Architect in the healthcare industry.

See salaries and explore the career path for Information Architect

User Experience Designer

A User Experience Designer designs and builds user interfaces that are easy to use and understand. These interfaces can include websites, software applications, and mobile apps. This course provides a strong foundation in the principles and techniques of user experience design, and would be particularly useful for someone who wants to work as a User Experience Designer in the healthcare industry.

See salaries and explore the career path for User Experience Designer

Software Engineer

A Software Engineer designs, builds, and maintains software applications. These applications can be used for a variety of purposes, such as data analysis, financial trading, and medical diagnosis. This course provides a strong foundation in the principles and techniques of software engineering, and would be particularly useful for someone who wants to work as a Software Engineer in the healthcare industry.

See salaries and explore the career path for Software Engineer

Data Scientist

A Data Scientist uses data science techniques to solve business problems. These problems can include fraud detection, spam filtering, and medical diagnosis. This course provides a strong foundation in the principles and techniques of data science, and would be particularly useful for someone who wants to work as a Data Scientist in the healthcare industry.

See salaries and explore the career path for Data Scientist

Health Information Manager

A Health Information Manager oversees the management of health information in a healthcare organization. This includes collecting, storing, and analyzing patient data. This course provides a strong foundation in the principles and techniques of health information management, and would be particularly useful for someone who wants to work as a Health Information Manager in the healthcare industry.

See salaries and explore the career path for Health Information Manager

Medical Librarian

A Medical Librarian helps healthcare professionals find and use information. This information can come from a variety of sources, such as books, journals, and databases. This course provides a strong foundation in the principles and techniques of medical librarianship, and would be particularly useful for someone who wants to work as a Medical Librarian in the healthcare industry.

See salaries and explore the career path for Medical Librarian

Quality Improvement Analyst

A Quality Improvement Analyst helps healthcare organizations improve the quality of care they provide. This includes collecting, analyzing, and interpreting data on patient outcomes. This course provides a strong foundation in the principles and techniques of quality improvement, and would be particularly useful for someone who wants to work as a Quality Improvement Analyst in the healthcare industry.

See salaries and explore the career path for Quality Improvement Analyst

Pharmacist

A Pharmacist dispenses medications and provides information about their use. This course provides a strong foundation in the principles and techniques of pharmacy, and would be particularly useful for someone who wants to work as a Pharmacist in the healthcare industry.

See salaries and explore the career path for Pharmacist