Researchers have unveiled an interpretable, lightweight AI text detection framework using classical machine learning models that achieves near-perfect accuracy while lowering computational costs.

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.

A new review in Science China Life Sciences examines how machine learning and host-microbiome multi-omics can be combined to better understand health and disease. The article outlines the road from ...

Researchers have developed a new methodology that uses artificial intelligence (AI) tools to identify and count target viruses more efficiently than previous techniques. The new approach can be used ...

Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...

Redis, the world’s fastest data platform, today announced Redis Feature Form, a managed feature store platform built to help enterprise ML teams bring features into production with more control, ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Abstract: Fuzzy support vector machine is a versatile machine learning technique for addressing binary classification and regression challenges. However, it still faces problems related to borderline ...

Abstract: The low graduation rate is not on time for student studies in higher education, which is a crucial issue that requires data-based solutions. This study aims to evaluate and compare the ...

In the first Trump administration, the U.S. launched a “maximum pressure” campaign to cut Iranian oil from the global market and eliminate Tehran’s biggest source of revenue. Today, Iran sells ...