Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, United States Introduction: Data sharing is essential for advancing research in radiation oncology, particularly for training artificial ...

Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...

Abstract: This study explores the use of supervised learning and Q-learning to optimize dynamic preamble allocation in a single-cell 5G network, supporting SDG 9 (Industry, Innovation, and ...

Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Recently, Aircela, a fuel company headquartered in New York, publicly demonstrated a machine in Manhattan that produces gasoline directly from air. The event attracted city and state officials, ...