Natural Language Processing to Improve Patient Care

The UBC Micro-certificate in Natural Language Processing equips healthcare professionals with essential skills in natural language processing (NLP) for healthcare contexts. Participants learn how to apply NLP tools and techniques to text-based data, such as clinical documents, patient records and medical reports, and use the insights gleaned to address real-world healthcare challenges, including improving quality of care, efficiency and decision-making. .

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

• Understand how natural language processing (NLP) techniques are used to analyze diverse types of healthcare data, including clinical documents and patient-generated content
• Implement core NLP tasks such as text pre-processing, named entity recognition, sentiment analysis and topic modelling to extract meaningful insights from health-related text
• Evaluate and leverage large language models (LLMs) and neural networks for healthcare applications, including summarization, classification, question answering and patient note analysis
• Identify patient needs and experiences by analysing unstructured data using sentiment and mood analysis
• Critically assess the reliability, accuracy and ethical implications of NLP outputs in clinical and patient-centred contexts, including awareness of model limitations, hallucinations and privacy considerations
• Design responsible, real-world NLP solutions that support clinical decision-making, health research and patient care optimizations

This program is designed for healthcare professionals, researchers, and clinical or operational staff at all career stages interested in learning more about NLP and generative AI tools and their applications for clinical and health data sets. It’s especially relevant for healthcare professionals pursuing career enhancement or advancement in clinical informatics, data science or health administration. Current or former students of the UBC Micro-certificate in Health Data Analytics: Opportunities and Applications may also be interested in this program.

Although not required, some data analysis experience and familiarity with basic data concepts is helpful. Physicians who complete this program may be eligible to receive Mainpro+/MOC credits.

Our students include:

• physicians
• nurses
• clinicians
• health administrators
• clinical or operational staff
• health researchers
• data scientists and data analysts new to NLP or healthcare

Each course costs $1,025. The total cost of the program is $3,075.

All fees are in Canadian dollars, subject to change and to GST (where applicable). For details on forms of payment accepted, please see How to pay.

Find more details on refunds, cancellations and transfers.

The micro-certificate program consists of three courses of five weeks each. Combined, the courses take approximately 75 hours to complete.

Courses can be taken on their own, in any order. If you’re new to NLP, we suggest starting with Overview of NLP and Large Language Models. While the micro-certificate can be earned regardless of course order, to gain the most value from the program we recommend taking courses in succession as they build upon one another.

1. Overview of NLP and Large Language Models (0573)
2. Extraction and Analysis of Clinical Documents (0574)
3. Analysis of User Generated Content (0575)

Required Courses

This part-time 100% online program is instructor supported and combines weekly real-time virtual office hours and independent study.

You can access online materials on your own time. Each week, you’ll have an opportunity to review readings and videos and apply your knowledge through multiple-choice quizzes and hands-on lab assignments. Students are also encouraged to contribute to an online discussion board where they can connect with one another and read feedback from the instructor/TA.

Expected effort

Expect to spend approximately five to seven hours per week completing all learning activities, including attending real-time online office hours.

Technology Requirements

To take this program, you need access to:

• an email account
• a computer, laptop or tablet, using Windows, macOS or Linux
• the latest version of a web browser (or previous major version release)
• a Google account to access Google Drive
• a reliable internet connection
• a video camera and microphone

Assessment

You are assessed on successfully completing lab assignments and multiple-choice quizzes, as well as your contributions to discussion posts. These activities are marked using a scoring rubric, and your instructor provides you with informal feedback on discussion posts. You must achieve a minimum of 70% in each course to earn your micro-certificate.

While your attendance at the weekly online office hours is not assessed, we encourage you to attend so you don’t miss the opportunity to learn and interact with your instructor and other participants.

Our program is co-developed by UBC leaders in medicine and data science, with input from BC regional health authorities, to meet the rising need for health care professionals with AI-based data analysis skills.

Dr. Raymond Ng, PhD is a professor of Computer Science at the University of British Columbia and the Director of the Data Science Institute. He is also the holder of the Canadian Research Chair on Data Science and Analytics. His research areas include data mining, text mining, health informatics, sensor analytics and databases.

Dr. Giuseppe Carenini, PhD is a professor of Computer Science at the University of British Columbia, an Amazon Scholar and the Director of the UBC Master of Data Science in Vancouver. His work on natural language processing and information visualization to support decision making has been published in over 160 peer-reviewed papers.

Saffrin Granby is a data scientist at Vancouver Coastal Health (VCH) and a co-founder of Autochart. She is passionate about integrating national language processing solutions and analytics into the healthcare system.

Dr. Lovedeep Gondara, PhD is a machine learning researcher, a former scientist at Provincial Health Services Authority (PHSA) and an adjunct professor at the School of Population and Public Health at the University of British Columbia. Dr. Gondara’s research work focuses on language models (large and small) and their applications in healthcare.

Dr. Richard Lester, MD, FRCPC is the director of the Neglected Global Diseases Initiative (NGDI) and an associate professor in Global Health in the Division of Infectious Diseases, Department of Medicine, at the University of British Columbia.