Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

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 ...

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...

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 ...

Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...