Please see the description and follow the RUBRIC below:
Assessment Description
The purpose of this assignment is to describe and evaluate machine learning processes and techniques used in health care. In a 750-1,000-word essay, address the following:
Describe the difference between labeled data sets and unlabeled data sets.
Describe the difference between supervised and unsupervised machine learning.
Select either supervised or unsupervised machine learning and discuss the types of analytic tools that are used to analyze data sets.
Discuss the types of analytic tools that are used to analyze data sets.
Discuss the rationale for selecting the analytic tool that was selected to analyze supervised vs. unsupervised machine learning.
Discuss the machine learning process?
Provide examples of the uses of machine learning in health care.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is located in Class Resources if you need assistance.
RUBBRIC:
Difference Between Labeled and Unlabeled Data Sets = 14
Difference Between Supervised vs. Unsupervised Machine – 7 points Learning assessment
Types of Analytic Tools Used to Analyze Data Sets 7 points
Rationale for Selecting Analytic Tool to Analyze Supervised vs. Unsupervised Machine Learning = 14 points
Machine Learning Process
14 points
Examples of the Uses of Machine Learning in Health Care
14 points
Thesis, Position, or Purpose = 7
Development, Structure, and Conclusion- 8
Evidence – 5
Mechanics of Writing assessment – 5
Format/Documentation – 5
READING MATERIALS that can be used as REFERENCE (more than 3 reference)
1. Prediction of Hospitalization Due to Heart Diseases by Supervised Learning Methods Read "Prediction of Hospitalization Due to Heart Diseases by Supervised Learning Methods," by Dai, Brisimi, Adams, Mela, Saligrama, and Paschalidis, from International Journal of Medical Informatics (2015).
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314395/
2. Machine Learning in Medicine: A Practical Introduction
Read "Machine Learning in Medicine: A Practical Introduction," by Sidey-Gibbons and Sidey-Gibbons, from BMC Medical Research Methodology (2019).
https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-019-0681-4
3. youtube videos:
thank you so much!
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