Breast cancer is one of the major causes of female death in any part of the world, and the burden is highly ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

Can Canada own the AI industry it helped invent? A new report explores AI sovereignty and the roadmap to changing our ...

Drug-drug interactions (DDI) can cause adverse drug reactions during the co-administration of multiple drugs, necessitating accurate and scalable prediction tools. While deep learning models have ...

Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

Tongue images and related clinical data were retrospectively collected from 120 HT patients (60 each from the euthyroid group and the hypothyroidism group), and the tongue region was segmented by ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Cloud classification is evolving into a central component of meteorological research and practical applications, including climate monitoring and solar energy forecasting. Recent advances in machine ...

Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...