Applying Bayesian Ridge Regression AI Modeling in Virus Severity
Prediction
- URL: http://arxiv.org/abs/2310.09485v3
- Date: Mon, 4 Dec 2023 21:11:45 GMT
- Title: Applying Bayesian Ridge Regression AI Modeling in Virus Severity
Prediction
- Authors: Jai Pal, Bryan Hong
- Abstract summary: We review the strengths and weaknesses of Bayesian Ridge Regression, an AI model that can be used to bring cutting edge virus analysis to healthcare professionals.
The model's accuracy assessment revealed promising results, with room for improvement.
In addition, the severity index serves as a valuable tool to gain a broad overview of patient care needs.
- Score: 0.0
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: Artificial intelligence (AI) is a powerful tool for reshaping healthcare
systems. In healthcare, AI is invaluable for its capacity to manage vast
amounts of data, which can lead to more accurate and speedy diagnoses,
ultimately easing the workload on healthcare professionals. As a result, AI has
proven itself to be a power tool across various industries, simplifying complex
tasks and pattern recognition that would otherwise be overwhelming for humans
or traditional computer algorithms. In this paper, we review the strengths and
weaknesses of Bayesian Ridge Regression, an AI model that can be used to bring
cutting edge virus analysis to healthcare professionals around the world. The
model's accuracy assessment revealed promising results, with room for
improvement primarily related to data organization. In addition, the severity
index serves as a valuable tool to gain a broad overview of patient care needs,
aligning with healthcare professionals' preference for broader categorizations.
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