Deep Learning for Biomedical Image Analysis

Advances in the AI method of deep learning have the potential to transform how biomedical data is analyzed for research, clinical diagnosis and prognosis. This nanocourse will deliver information and allot guided practice so that anyone can apply the principles and algorithms of deep learning to process and analyze their own biomedical images. The purpose of the course is to deliver practical knowledge of deep learning for image analysis including possibilities, current limitations and challenges. Participants with and without programming experience are encouraged to attend!

Topics include: fundamentals of deep learning, methods for segmentation, classification, automated analysis and knowledge discovery from biomedical imaging data as well as methods to combine information from multiple data sources such as microscopy and genomic data.

By the end of this nanocourse, students should be able to:
1. Determine whether deep learning is appropriate for their research needs/ projects
2. Apply principles and algorithms of deep learning to analyze their own biomedical images
3. Read and understand literature about deep learning
4. Name some limitations and potential future applications of deep learning

All are welcome for the lecture portions of this nanocourse:
Tuesday February 11, 2020, from 2-4pm in Cannon Room (Building C)
Wednesday February 12, 2020, from 2-4pm in Cannon Room (Building C)
Thursday February 13, 2020, from 2-4pm in Cannon Room (Building C)

Registration is required for the hands-on portion of this nanocourse, where we will apply deep learning to participants' real data**:
Friday February 21, 2020, from 2-4pm in TMEC L-007

**In order to receive course credit, you must register for this course below and you must attend all 4 sessions and complete all assignments. Please note that registration is capped at 24 students.

Course director: Davie Van Vactor, Dept. of Cell Biology
Instructor: Faisal Mahmood, Dept. of Computational Pathology
Curriculum Fellow: Saoirse McSharry, saoirse_mcsharry@hms.harvard.edu

* Note: the workshop for this nanocourse is full, so you will be placed on the waitlist for that session, but you are still welcome to attend the sessions on February 11-13th, 2020.