In this tutorial, we explore how we can decode linguistic features directly from brain signals using a modern neuroAI pipeline. We work with MEG data and build an end-to-end system that transforms raw ...

A new study finds that certain patterns of AI use are driving cognitive fatigue, while others can help reduce burnout. by Julie Bedard, Matthew Kropp, Megan Hsu, Olivia T. Karaman, Jason Hawes and ...

Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...

However, previous studies did not systematically synthesize their diagnostic accuracy. Objective: To quantitatively explore the diagnostic efficacy of deep learning (DL) and radiomics for extracranial ...

Deep learning has become a transformative technology for modern weed detection, offering significant advantages over traditional machine vision in robustness, scalability, and recognition accuracy.

5,572 SMS messages. 747 spam. Can a custom neural network compete with BERT? This project compares three deep learning approaches to SMS spam detection: a custom LSTM architecture built from scratch, ...

Deep Learning Crash Course: A Hands-On, Project-Based Introduction to Artificial Intelligence is written by Giovanni Volpe, Benjamin Midtvedt, Jesús Pineda, Henrik Klein Moberg, Harshith Bachimanchi, ...

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...