Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, enabling researchers to process large volumes of environmental data and satellite ...

Sight, Deep Learning, Convolutional Neural Network, Long Short-Term Memory, Self-Attention Mechanism Share and Cite: Li, G. , Wei, G. and Xi, Z. (2026) UWB NLOS Signal Recognition Based on Deep ...

A retinal image could help doctors quickly distinguish between similar neurodegenerative diseases, such as ALS and Alzheimer's disease, and with remarkable accuracy, according to new research ...

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 ...

MIT researchers have developed a generative artificial intelligence-driven approach for planning long-term visual tasks, like robot navigation, that is about twice as effective as some existing ...

To use this evidence, investigators typically must grow the larvae until adulthood in a laboratory setting and then identify ...

Combining gait, handwriting, and speech analysis, this AI framework enhances early Parkinson's disease detection, addressing clinical challenges effectively.

The startup’s software-as-a-medical (SaMD) determines a predicted delivery date solely from standard ultrasound images.

Abstract: This research explores a deep learning-based approach to sports image classification using four convolutional neural network (CNN) models: VGG-16, VGG-19, Xception, and EfficientNetB7. The ...

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

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 ...