Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Applied Statistics (1)
- Artificial Intelligence and Robotics (1)
- Cardiovascular Diseases (1)
- Categorical Data Analysis (1)
- Collection Development and Management (1)
-
- Computer Engineering (1)
- Computer Sciences (1)
- Data Science (1)
- Databases and Information Systems (1)
- Disease Modeling (1)
- Diseases (1)
- Engineering (1)
- Health Sciences and Medical Librarianship (1)
- Institutional and Historical (1)
- Library and Information Science (1)
- Medicine and Health Sciences (1)
- Numerical Analysis and Scientific Computing (1)
- Other Computer Engineering (1)
- Programming Languages and Compilers (1)
- Science and Technology Studies (1)
- Social and Behavioral Sciences (1)
- Statistical Methodology (1)
- Institution
Articles 1 - 2 of 2
Full-Text Articles in Statistical Models
Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth
Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth
Electronic Theses, Projects, and Dissertations
The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of severe chronic and cardiovascular complications if left untreated. This study investigated the causes and underlying risks of hypertension in females aged between 18-39 years. The research questions were: (Q1.) What factors affect the occurrence of hypertension in females aged 18-39 years? (Q2.) What machine learning algorithms are suited for effectively predicting hypertension? (Q3.) How can SHAP values be leveraged to analyze the factors from model outputs? The findings are: (Q1.) Performing Feature selection using binary classification Logistic regression algorithm reveals an array of 30 most influential factors at an …
Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney
Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney
Computer Science and Software Engineering
Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.