Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Over the last several decades, urban planners and municipalities have sought to identify and better manage the socioeconomic dynamics associated with rapid development in established neighborhoods.

Firms integrating AI and machine learning into their investment processes are building compounding advantages that late adopters may never overcome.

Rules-based automation (RBA) and learning are two training mechanisms in robotics. While there are many others, these are two ...

AI algorithms analyse complex medical images with speed and precision, supporting early disease detection.Radiology and ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

Musculoskeletal (MSK) conditions drive a large share of global pain, disability, and lost productivity. Rehabilitation can be effective, but outcomes vary ...

The “one big breakthrough” pattern suggests that total citation counts can mislead. A researcher with one highly-cited paper and several uncited ones may have a more impactful trajectory than one with ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.

A new publication from Opto-Electronic Technology; DOI   10.29026/oet.2025.250010, discusses how a photonic vibration ...