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Posted: March 16th, 2022
10-15 Slides
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.
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 Providers.
The HIPAA Privacy Rule.
New Machine Learning Approach Supports Patient Data Privacy.
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