Air pollution is a critical global environmental issue, further exacerbated by rapid industrialization and urbanization. Accurate prediction of air pollutant concentrations is essential for effective ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Culture-independent 16S rRNA gene metabarcoding is a commonly used method for microbiome profiling. To achieve more quantitative cell fraction estimates, it is important to account for the 16S rRNA ...

Traditional deep learning is not suited to understanding dynamic systems that change regularly as a function of time, like firing neurons or flowing fluids. These patterns of activity are so complex ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...