By integrating large-kernel convolutional blocks and a novel loss function, LKNet effectively addresses challenges such as ...

Federal agents raided a large cannabis farm in Southern California on Thursday, clashing with protesters and arresting multiple people, the latest confrontation in a state that has become a ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...

We have carefully reviewed the article titled ‘Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study’ by ...

Intermountain Health is deploying Layer Health’s artificial intelligence for clinical data abstraction to improve its quality reporting and clinical registry submissions in stroke, surger ...

The decision in Recentive Analytics v. Fox Corp. is significant for patent attorneys and applicants in the AI space, particularly those seeking protection for inventions that incorporate machine ...

Artificial intelligence (AI) refers to machine-based systems that analyze input data to generate predictions, recommendations, or decisions, 1 AI-based and machine learning (ML)-based technologies ...

Deep learning breakthrough enhances crop disease detection across lab and field Plant diseases remain a major threat to food security and agricultural productivity, especially in resource-constrained ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

In this work, we present an approach that integrates theoretical spectral calculations with machine learning to identify PAHs, an approach that can be extended straightforwardly to the thousands of ...