Week 9-28 - Ontologies and Machine Learning

These two lectures this week were packed full of information.  Both had subjects that could be taught easily over several class periods but I understand this course is about getting exposure to the various methods and we can't go into depth.  I think Dr. Fridsma stated it best in the town hall meeting --- in 502, you are exposed to a lot of new information but to fully understand it you have to spend hours researching to grasp the understanding. The content being taught is synonymous to learning a new language.

The syntactic versus semantic discussion made sense and the lecture for ontologies made a little more sense than the first round. Probably the best slide illustrating the differences in semantic and syntactic was slide # 30 with the following statement:  "The ability of multiple systems to exchange information and to be able to use the information that has been exchanged."  From a healthcare perspective, this is what decision support is all about.  We need to pull information from disparate system together use the information to evaluate trends and suggest alternative paths if necessary.

Machine learning is interesting for data mining.  This is another which appears to be very complex but hugely important in data analysis.  This lecture, in my opinion, was a little better to understand.  There were concrete examples and nice tutorials to show how certain models worked and the instructor helped by restating the concepts several times.  I understand the supervised versus unsupervised and the K nearest versus the K means.  Other than that, the other models made sense but I'm having a hard time trying to understand how these are applied in real situations.  It would be nice to take concrete data sets and run them through a few of these models in class.   The student grouping for the clustering example is a good example of how to illustrate the different models but still very hard to keep it all straight.

These as well as other lectures have been full of information but it would be nice to apply some of what we learn into some real applications during the class instead of having just lectures without any hands on or real-world application.
Posted by :  Debbie Carter