f11Stat841proposal: Difference between revisions
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==Project 1 : Title == | ==Project 1 : Title == Classification of Disease Status | ||
</noinclude> | </noinclude> | ||
===By: | ===By: Lai,ChunWei and Greg Pitt=== | ||
For our classification project, we are proposing an application in the | |||
medical diagnosis field: For each patient or lab animal, there will | |||
be results from a large number of genetic and/or chemical tests. We | |||
should be able to predict the disease state of the patient/animal, | |||
based on the presence or absence of certain biomarkers and/or chemical | |||
markers. | |||
Our project work will include the reduction of dimensionality, and the | |||
development or one or more classification functions, with the | |||
objectives of minimizing the error rate and also reducing the number | |||
of markers required in order to make good predictions. Our results | |||
could be used at the patient level, to help make accurate diagnoses, | |||
and at the population health level, to make epidemiological surveys of | |||
the prevalence of certain medical conditions. In both cases, the | |||
results should enable the healthcare system to make better decisions | |||
regarding the deployment of scarce healthcare resources. | |||
Our methodology will be chosen soon, after we have seen a few more | |||
examples in class. If time permits, we will also attempt a novel | |||
classification procedure of our own design. | |||
Currently we have access to a dataset from the SSC data mining | |||
section, and we hope to be able to get access to some similar, but | |||
larger, datasets before the end of the term. | |||
The software tools that we use will probably include Matlab, Python, and R. | |||
We would like to obtain publishable results if possible, but this is | |||
not a primary objective. | |||
<noinclude> | <noinclude> | ||
Revision as of 19:19, 3 October 2011
==Project 1 : Title == Classification of Disease Status
By: Lai,ChunWei and Greg Pitt
For our classification project, we are proposing an application in the medical diagnosis field: For each patient or lab animal, there will be results from a large number of genetic and/or chemical tests. We should be able to predict the disease state of the patient/animal, based on the presence or absence of certain biomarkers and/or chemical markers.
Our project work will include the reduction of dimensionality, and the development or one or more classification functions, with the objectives of minimizing the error rate and also reducing the number of markers required in order to make good predictions. Our results could be used at the patient level, to help make accurate diagnoses, and at the population health level, to make epidemiological surveys of the prevalence of certain medical conditions. In both cases, the results should enable the healthcare system to make better decisions regarding the deployment of scarce healthcare resources.
Our methodology will be chosen soon, after we have seen a few more examples in class. If time permits, we will also attempt a novel classification procedure of our own design.
Currently we have access to a dataset from the SSC data mining section, and we hope to be able to get access to some similar, but larger, datasets before the end of the term.
The software tools that we use will probably include Matlab, Python, and R.
We would like to obtain publishable results if possible, but this is not a primary objective.