Week 10 Assignment – Machine Learning Applied to Data Privacy Due: Mon Sep 11, 2

Week 10 Assignment – Machine Learning Applied to Data Privacy
Due: Mon Sep 11, 2023 9:00amDue: Mon Sep 11, 2023 9:00amUngraded, 175 Possible Points175 Possible PointsAttempt
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Overview
In this assignment you will examine how machine learning can be applied in health care. The advent of interoperability and telehealth present the opportunity to apply machine learning to a wide variety of practices and services in health care. Machine learning models use large datasets to help providers diagnose and treat illness and potentially improve the prognosis for the patient. The increased use of machine learning in health care increases the need to protect patient information. Machine learning can be used to protect patient information. You will develop a PowerPoint presentation to establish how machine learning is applied to patient care and the protection of patient information.
Instructions
Prepare a 10-15-slide PowerPoint presentation with detailed scholarly speaker notes in which you:
Establish how concepts of machine learning are applied in health care. Support with examples.
Differentiate how the three types of machine learning—supervised learning, unsupervised learning, and reinforcement learning—could be applied in health care. Support with examples.
Determine three different situations where machine learning could be applied in health care.
Propose how machine learning could be used to protect patient information in three identified situations.
Propose how machine learning could be applied to improve health care delivery for both the patient and the provider in three identified situations.
Use at least three sources to support your writing. Choose sources that are credible, relevant, and appropriate. Cite each source listed on your source page at least one time within your assignment. For help with research, writing, and citation, access the library or review library guides.
This course requires the use of Strayer Writing Standards (SWS). The library is your home for SWS assistance, including citations and formatting. Please refer to the Library site for all supports. Check with your professor for any additional instructions.
The specific course learning outcome associated with this assignment is:
Propose how contemporary HIMS technologies and concepts can be applied to improve health care delivery through health care information.
Resources
Top 4 Machine Learning Use Cases for Healthcare ProvidersLinks to an external site..
The HIPAA Privacy Rule.Links to an external site.
New Machine Learning Approach Supports Patient Data PrivacyLinks to an external site..
View Rubric
Week 10 Assignment – Machine Learning Applied to Data Privacy
Week 10 Assignment – Machine Learning Applied to Data Privacy
CriteriaRatingsPts
Establish how concepts of machine learning are applied in health care. Support with examples.view longer description
28 to >25.2 pts
Exemplary
Established how concepts of machine learning are applied in healthcare. Supported with examples.25.2 to >22.4 pts
Competent
Established how concepts of machine learning are applied in health care but not supported with examples.22.4 to >19.6 pts
Needs Improvement
Established how concepts of machine learning are applied but not in health care.19.6 to >0 pts
Unacceptable
Did not submit or establish how concepts of machine learning are applied in health care that are supported with examples./ 28 pts
Differentiate how three types of machine learning could be applied in health care. Support with examples.
view longer description
28 to >25.2 pts
Exemplary
Differentiated how three types of machine learning could be applied in health care. Supported with examples.25.2 to >22.4 pts
Competent
Differentiated how three types of machine learning could be applied in health care but not supported with examples.22.4 to >19.6 pts
Needs Improvement
Differentiated how two types of machine learning could be applied in health care that are supported with examples.19.6 to >0 pts
Unacceptable
Did not submit or differentiate how three types of machine learning could be applied in health care that are supported with examples./ 28 pts
Determine three different situations where machine learning could be applied in health care.
view longer description
28 to >25.2 pts
Exemplary
Determined three different situations where machine learning could be applied in health care.25.2 to >22.4 pts
Competent
Determined two different situations where machine learning could be applied in health care.22.4 to >19.6 pts
Needs Improvement
Determined one situation where machine learning could be applied in health care.19.6 to >0 pts
Unacceptable
Did not submit or determine three different situations where machine learning could be applied in health care./ 28 pts
Propose how machine learning could be used to protect patient information in three identified situations.
view longer description
28 to >25.2 pts
Exemplary
Proposed how machine learning could be used to protect patient information in three identified situations.25.2 to >22.4 pts
Competent
Proposed how machine learning could be used to protect patient information in two identified situations.22.4 to >19.6 pts
Needs Improvement
Proposed how machine learning could be used to protect patient information in one identified situation.19.6 to >0 pts
Unacceptable
Did not submit or propose how machine learning could be used to protect patient information in three identified situations./ 28 pts
Propose how machine learning could be applied to improve health care delivery for both the patient and the provider in three identified situations.
view longer description
28 to >25.2 pts
Exemplary
Proposed how machine learning could be applied to improve health care delivery for both the patient and the provider in three identified situations.25.2 to >22.4 pts
Competent
Proposed how machine learning could be applied to improve health care delivery for both the patient and the provider in two identified situations.22.4 to >19.6 pts
Needs Improvement
Proposed how machine learning could be applied to improve health care delivery for both the patient and the provider in one identified situation.19.6 to >0 pts
Unacceptable
Did not submit or propose how machine learning could be applied to improve health care delivery for both the patient and the provider in three identified situations./ 28 pts
Use at least three sources to support your writing. Choose sources that are credible, relevant, and appropriate. Cite each source listed on your source page at least one time within your assignment.
view longer description
17.5 to >15.75 pts
Exemplary
Cited at least three credible, relevant, and appropriate sources; each source was cited within the assignment.15.75 to >14 pts
Competent
Cited required number of sources but not all sources were credible, relevant, or appropriate; or sources were not cited within the assignment.14 to >12.25 pts
Needs Improvement
Did not cite the required number of sources or cited required number of sources but sources were not credible, relevant, or appropriate.12.25 to >0 pts
Unacceptable
Did not cite any sources./ 17.5 pts
Produce writing that contains accurate grammar, mechanics, and spelling in accordance with SWS style.
view longer description
17.5 to >15.75 pts
Exemplary
Produced writing that is clear and well organized and applies appropriate SWS style. Writing contains accurate grammar, mechanics, and spelling with 0-2 errors.15.75 to >14 pts
Competent
Produced writing that attempts to be clear and well organized and to apply appropriate SWS style. Writing contains some errors in grammar, mechanics, and spelling. There may be occasional errors (1-2), but they do not impact the ability of the reader to understand the writing.14 to >12.25 pts
Needs Improvement
Produced writing that has noticeable issues with clarity, organization, and the application of SWS style. Writing contains some errors in grammar, mechanics, and spelling. There are multiple errors (3-4) that distract from the reader’s ability to understand the writing.12.25 to >0 pts
Unacceptable
Produced writing that lacks clarity, organization, or does not apply SWS style. There are significant issues with grammar, mechanics, and spelling. Overall, errors are significant in number (5 or more), and the reader will have difficulty understanding the writing./ 17.5 pts
Total Points: 0
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