A new “periodic table for machine learning,” is reshaping how researchers explore AI, unlocking fresh pathways for discovery.

Chinese Academy of Sciences (CAS), has developed a machine learning (ML) model enhanced with expert knowledge to classify ...

MACHINE learning could reshape how clinicians assess focal bone lesions, offering a more consistent and data-driven ...

Rice researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially ...

Researchers in Singapore and the US have independently developed two new types of photonic computer chips that match existing ...

The main purpose of this project was to build a CNN model that would classify if the subject has a tumor or not based on MRI scan using deep learning ... the model for this binary problem. This ...

An automated machine-learning program developed by researchers from Edith Cowan University (ECU) in conjunction with the ...

In the ever-growing field of machine learning, one of the most significant challenges is making complex models interpretable and accessible. Enter AutoXplainAI, an innovative framework developed by ...

Researchers at the University of Houston and the University of Cincinnati are using machine learning to create a clearer ...

Using machine learning, researchers automatically calibrate a comprehensive climate model, improving simulations of difficult features and taking steps toward more reliable climate projections.

An automated machine learning program has been able to identify potential cardiovascular incidents or fall and fracture risks based on bone density scans taken during routine clinical testing.

Researchers from Nanjing University and Carnegie Mellon University have introduced an AI approach that improves how machines learn from past data—a process known as offline reinforcement learning.