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Course Announcement: NLP and Large Language Models for Health and Medicine

DataLab Faculty Director Professor Vladimir Filkov and affiliate Professor Nick Anderson are teaching a new seminar course this spring: ECS 289G: Natural Language Processing and Large Language Models for Health and Medicine.

Course Information:
CRN: 63185
Lectures: Friday, 11 – 12:30 pm, starting April 7.
Location: DataLab classroom, 3rd Floor of Shields Library, Room 360 (lecture room), UC Davis Campus

Course Goals: NLP and most recently LLMs (Large Language Models) have shown tremendous promise in bridging the gap between computers and humans, by providing almost human level processing and even understanding of spoken language. That ability has been in turn translated into automation of tasks hitherto thought reserved for human intellect: complex pattern recognition, language translation, code generation, recommendation systems, or interactive expert training.

The goal of this seminar course is to read and discuss the application of Natural Language Processing (NLP) and Large Language Models (LLMs) in medical and health applications. Specific goals will be to understand use cases for NLP and LLMs in medicine and research, identify state of the art methods and tools, and identify the research horizon and the sociotechnical and ethical obstacles in this domain.  

We will meet each week for 1.5 hours, and have sessions on critical presentation and review of the literature, followed by discussions. Registered students will be expected to be prepared to discuss each week’s assigned papers, and will be expected to present and guide the discussion for at least one paper, in person.

Instructors: Prof. Vladimir Filkov (Computer Science/DataLab), Prof. Nick Anderson (Public Health Sciences)

Textbook: No textbook. Slides and scientific papers will be used.

Prerequisites: 1st year grad student or permission of instructor. Research interests in socio-technical domains including computer science, information science, informatics, digital communications, public health, medicine.

Units: 1 or 2 units.

Course Expectations:

Paper critique and participation: Each student will expect to be prepared to lead and deliver formal paper review each week, discussing in detail an assigned paper from the reading list. Deadlines will be shown on the schedule, and students will be selecting/selected for presentation shortly before each session.

Expectations of work: Students should expect to be spending 3-6 hours outside the classroom each week reading and generating critique on assigned papers. 

Exams: No exams will be given

Grading: Pass/No Pass

For more information, contact Vladimir Filkov.

Category

Education

Tags

Courses Health Data Science Large Language Models LLM Natural Language Processing NLP public health Seminars