Abstract: This study utilizes decision tree and logistic regression models to explore the factors contributing to medical claim denials and identify areas for improvement. We adapt undersampling ...
From the first 5 rows of the dataset, we can see that there are several columns available: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, and sex. There also appears ...
1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Background: Aspiration pneumonia is a serious complication after cardiac surgery, particularly among older patients. Preoperative oral frailty—decline in oral function including poor hygiene and ...
Objective: To develop and validate a logistic regression model predicting postoperative malnutrition risk in elderly patients using clinical, dietary, and nutritional data. Table 1. Comparison of ...
Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...
The aim is to build a simple classification model for the given case scenario. The problem statement and the supporting dataset are attached for your reference. After building the classification model ...
ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...
Background: This study aimed to evaluate the predictive utility of routine hematological, inflammatory, and metabolic markers for bacteremia and to compare the classification performance of logistic ...