Summary of Predicting Diabetes with Machine Learning Analysis Of Income and Health Factors, by Fariba Jafari Horestani et al.
Predicting Diabetes with Machine Learning Analysis of Income and Health Factors
by Fariba Jafari Horestani, M. Mehdi Owrang O
First submitted to arxiv on: 20 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The study explores the connection between diabetes and various health indicators, focusing on income as a newly added factor. The researchers analyzed data from the 2015 BRFSS to investigate how different factors like blood pressure, cholesterol, BMI, smoking habits, and others impact diabetes prevalence. They examined each factor individually and in combination with income, using statistical and machine learning techniques to uncover the intricate relationships between socio-economic status and diabetes risk. The findings reveal a notable trend where lower-income brackets are associated with a higher incidence of diabetes. Key features like high blood pressure, high cholesterol, cholesterol checks, income, and BMI were identified as crucial factors in diabetes prevalence and management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Diabetes is a major health concern that’s linked to many other health issues. This study looks at how different things like blood pressure, sugar levels, and lifestyle choices affect the risk of getting diabetes. The researchers used big data from 2015 to see what happens when they mix all these factors together. They found that people with lower incomes are more likely to get diabetes. Some important things they discovered include that high blood pressure, high cholesterol, and being overweight can increase the risk of diabetes. |
Keywords
» Artificial intelligence » Machine learning
