A large meta-analysis led by Northeastern University found that machine learning models can predict mental health treatment outcomes with about 76% accuracy. Reviewing 155 studies, researchers saw ...

MIT postdoctoral associate Arunav Kumar discusses his work on magnetohydrodynamic stability, plasma control in tokamaks, and ...

An AI model applied to pathology slides accurately predicts immunotherapy response in patients with metastatic non-small cell ...

Finally, during late spring and summer 2023, seagrass expanded rapidly. By July 2023, it covered more than 20% of the lagoon – levels not observed in more than a decade. Coverag ...

A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response ...

Machine learning (ML)-based clinical decision support (CDS) in the intensive care unit (ICU) has the potential to improve medical decision-making and patient outcomes. The chasm between model ...

Abstract: Hierarchical Federated Learning (HFL) has emerged as a promising paradigm for distributed machine learning in edge computing environments. By introducing intermediate edge servers between ...

This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates Random Forest ...

Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...

Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...