Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

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

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 ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

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 ...

As instigators of immunity, monoclonal antibodies are marvels of modern medicine, lab-made proteins that can treat cancers, ...