Seoul National University Hospital researchers have developed an AI model that predicts the response to an anticonvulsant ...
Abstract: In this study, we investigate multilingual and multiclass sentiment classification by analyzing datasets in Turkish, English, and Italian. The proposed approach consists of three main stages ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
(NASDAQ: NXXT ), a pioneer in AI-driven energy innovation transforming how energy is produced, managed, and delivered, today ...
Abstract: All the symptoms have been analyzed using several machine learning algorithms for diagnosing breast cancer. This paper utilizes the Breast Cancer Wisconsin (Diagnostic) data set to show how ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
However, the absence of validated predictive models remains a significant challenge. Objective: This study compared a conventional logistic regression model with machine learning (ML) models using ...
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