Prediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning Techniques to Resolve Class Imbalance
Official website of Novus Medical Research: https://www.newboat.top Our courses are better than Dingxiangyuan!
Novus Medical Research Learning PC version: https://app.newboat.top/, which contains a high-quality database, data extraction tools, and other resources, plus AI accounts.
Novus Medical Research Learning Mini Program: Novus Bear
Bilibili: Corresponding explanatory video for the article is here. Novus Medical Learning Community | Novus Medicine https://space.bilibili.com/475774512
WeChat Official Account | Bilibili | Douyin | Xiaohongshu | Zhihu | All with the same name: Novus Medical Research. Formerly Novus Learning Community.
Course Related Materials:
(1) Prediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning Techniques to Resolve Class Imbalance, follow the official account Novus Medical Research, reply with 2501c1 to get the resource link. Materials have been uploaded to the mini program:
(2) Custom Data Analysis, Core and SCI Journal Recommendations, please scan the code for consultation with the course assistant.
(3) Novus Medical Research Learning Center is officially launched! Many courses are free! Course members can easily learn all or specialized courses without worry; All-in-One members can also get course materials, premium source code, offline databases, medical data, and other quality resources for free. Thesis guidance students can receive a one-year All-in-One membership for free.
(4) Medical Public Data Database Learning Camp has opened classes, click to learn more.
Learn more | Medical Public Database Learning Camp
(5) Follow Novus Medical Research, formerly Novus Learning Community. Your support is my greatest motivation.
1 Introduction to the Paper
Title: Prediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning Techniques Resolving Class Imbalance
Diabetes is the most common and fastest-growing disease, affecting a large population across various age groups each year, shortening life expectancy. The high incidence rate increases the significance of early diagnosis. Diabetes can also lead to other complex complications, such as cardiovascular diseases, renal failure, stroke, and damage to vital organs. Early diagnosis of diabetes can reduce the likelihood of it progressing to chronic and severe states. Identifying and analyzing risk factors associated with different attributes of the spine helps determine the prevalence of diabetes in medical diagnostics.
Measuring and recognizing early diabetes prevalence lowers the chances of future complications. In this study, data from the NHANES dataset covering 1999-2000 to 2015-2016 was used. The aim of this research is to analyze and identify potential risk factors associated with diabetes through logistic regression and variance analysis, and to identify anomalies using various supervised machine learning algorithms. Class imbalance and anomaly issues were addressed, and experimental results indicated that age, blood-related diabetes, cholesterol, and BMI are the most significant risk factors associated with diabetes. Meanwhile, the random forest classification method achieved the highest accuracy score of .90.
Source code screenshot
2 Figures and Tables of the Paper
Figure 1: Identifying and Handling Outliers
Figure 2: Graphical Representation of the Models Used
Figure 3: Feature Importance Based on ANOVA F-scores
Figure 4: Structure of Artificial Neural Network (ANN)
Table 1: p-values, Odds Ratios, and Confidence Intervals Using Logistic Regression for Individual Risk Factors
Table 2: Comparison of Accuracy and AUC Scores at Different CV Values
Conclusion
(1) Prediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning Techniques to Resolve Class Imbalance, follow the official account Novus Medical Research, reply with 2501c1, to get the resource link. Materials have been uploaded to the mini program:
(2) Custom Data Analysis, Core and SCI Journal Recommendations, please scan the code for consultation with the course assistant.
(3) Novus Medical Research Learning Center is officially launched! Many courses are free! Course members can easily learn all or specialized courses without worry; All-in-One members can also get course materials, premium source code, offline databases, medical data, and other quality resources for free. Thesis guidance students can receive a one-year All-in-One membership for free.
(4) Medical Public Data Database Learning Camp has opened classes, thesis guidance elite class students can get recommended reviewer information, welcome to consult the course assistant!
Learn more | Medical Public Database Learning Camp
(5) Data Extraction and Custom Data Analysis, please scan the code for consultation with the course assistant.
(6) Video Course Recommendations