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| 09/08 - 12/18 | ||||||
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5:45 pm |
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Subject: Software Eng (Grad) (SEIS)
CRN: 40644
Online: Sync Distributed | Lecture
Online
Requirements Met:
Software Data Mgmt Conc
Software Technical Elective
The healthcare data is inherently heterogeneous with numeric health records, semi-structural medical text, and medical images. This course will discuss how to apply the latest artificial intelligence approaches in analyzing different types of healthcare data. Real-world projects to be discussed in this course include (1) training artificial intelligence models to learn patterns from 16-million medical papers and doctors’ notes for predicting potential disease outcomes, (2) analyzing patient health records to detect frequent medical sequences for treatment and prevention (3) applying machine vision methods in analyzing fish embryo images for identifying morphological changes due to toxic chemical exposure, (4) using deep-learning methods to analyze motions in telemedicine videos, (5) building clinic decision support systems to detect possible prescription errors, (6) querying databases on National Library of Medicine to enhance medical decisions, (7) imputing medical data with up to 95% missing values. Prerequisites: SEIS 639 or SEIS 764
3 Credits