Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

As anti-reservation sentiments grow, only data, facts and accurate information can provide solutions, says professor in ...

Harvard University is now offering free online Computer Science courses, making Ivy League education accessible to all. These self-paced courses, avai ...

Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional machine learning ...

To enhance cross-platform compatibility, we developed a Python version of ICLabel that uses standard EEGLAB data structures. We compared ICLabel MATLAB and Python implementations to data from 14 ...

Multiclass data sets and large-scale studies are increasingly common in omics sciences, drug discovery, and clinical research due to advancements in analytical platforms. Efficiently handling these ...

This study introduces an ensemble classification framework to detect and grade diabetic retinopathy into 5 classes leveraging the concepts of transfer learning and data fusion. It utilizes three ...

You need to know where your data is, what it is, its governance requirements and relationship to the rest of your data. We look at data classification and how AI can help ...