We developed precompiled lexicons and classification rules as features for the following ML classifiers: logistic regression, random forest, and support vector machines (SVMs). These features were ...

Traditional machine learning models for automatic information classification require retraining data for each task. Researchers have demonstrated that art data can be automatically classified with ...

Artificial intelligence is emerging as a powerful tool for improving the diagnosis, phenotyping, and treatment of ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A conversation with Professor Miraz Rahman, Head of the Department of Drug Discovery at King’s College London.