By applying techniques from explainable artificial intelligence, engineers can improve users' confidence in forecasts ...

Traditional biodiversity monitoring methods, such as direct observations and morphological classifications, often fall short ...

There is a critical need for noninvasive and reliable neuroimaging biomarkers to facilitate the early detection of neurological and psychological disorders, ...

Demystifying Artificial Intelligence in Data Pipelines As Artificial Intelligence (AI) continues to integrate into various ...

Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...

In a significant breakthrough, researchers have developed an advanced explainable deep learning model to predict and analyze harmful algal blooms (HABs) in freshwater lakes and reservoirs across China ...

As nuclear energy ramps up to move towards decarbonization goals, machine learning and AI techniques offer potential to speed ...