Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

The demand for AI human resources in Vietnam is exploding. TopDev reports continuously show that AI/Machine Learning is a ...

These were split into categories and their correlation with hypertension in this cohort was assessed using multivariate logistic regression. Python with libraries Numpy, Pandas, Scipy, Statsmodels, ...

Abstract: Programming language pre-training models have made significant progress in code representation learning in recent years. Although various methods, such as data flow and Abstract Syntax Tree ...

. ├── app/ # FastAPI application ├── train/ # Training scripts ├── assets/images/ # Images, diagrams ├── requirements.txt # Python dependencies ├── Dockerfile ├── .env.dist # Sample environment ...

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 ...

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ABSTRACT: In order to solve the problem of chronic heart failure risk prediction in the elderly, a logistic regression modeling framework with Bayesian method was proposed, aiming to solve the problem ...

Abstract: The purpose of this work is to investigate the effectiveness of DensNet and Logistic Regression in terms of accurately predicting the classification of footwear trends.In this study, there ...