and the validity of the model is verified. It can quickly identify the similarity between music or music groups based on music features. Based on the analysis and mining of ICM data, the ...

Abstract: This study makes significant contributions to the field by examining the transformative role of big data and artificial intelligence (AI) in advancing Sustainable Development Goals ... Using ...

As software and hardware capabilities increased, large amounts of data became storable and more easily accessed for analysis ... algorithms used to identify outliers are: Time series modeling ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data ... Automatic sentiment analysis of social media has ...

What are machine learning algorithms? Recall that machine learning is a class of methods for automatically creating models from data ... principal component analysis to convert correlated ...

Conducting a Bayesian data analysis - e.g. estimating a Bayesian linear regression model - will usually require some form of Probabilistic Programming Language (PPL). More often than not, PPLs ...

Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) ...

Routinely collected PROs contain added prognostic information not captured by an EHR-based ML mortality risk algorithm ... prediction model for individual prognosis or diagnosis (TRIPOD; Data ...