Lung cancer is a major global health concern, being one of the most common and fatal
cancers. Accurate early detection and prediction of lung cancer are crucial for improving …

Optimizing pricing strategies in e-commerce through machine learning is crucial for
enhancing customer satisfaction and achieving business success. This study evaluates the …

Software is increasingly vital, with automated systems regulating critical functions. As
development demands grow, manual code review becomes more challenging, often making …

This study explores the effectiveness of various machine learning algorithms in predicting
the success of cybersecurity attacks by analyzing historical attack data. We evaluated five …

This study investigates the application of sentiment analysis to customer feedback in the
banking sector, utilizing natural language processing (NLP) techniques and machine …

Customer segmentation is a critical strategy in the banking sector, enabling banks to tailor
their products and services to meet the diverse needs of their customer base. This study …

This study investigates the effectiveness of various machine learning models in predicting
product demand based on customer satisfaction data. Four models—Linear Regression …

Effective demand forecasting is vital for inventory management in retail. This study evaluates
five machine learning models—Linear Regression (LR), Decision Tree Regressor (DTR) …

This study explores the application of sentiment analysis in the banking sector, focusing on
customer feedback to enhance service quality and customer experiences. We collected a …

This study evaluates the effectiveness of statistical and machine learning models in credit
risk assessment, comparing traditional methods like logistic regression with advanced …