Spread the love“`html In the ever-evolving landscape of productivity tools, Notion has carved out a significant niche. With the introduction of Notion AI, users are now equipped with an intelligent ...

We introduce a biologically inspired bird-flocking experimental framework for text summarization that identifies the most salient sentences using contextual information, sentence position, and ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Conclusions: Text-based depression estimation models trained with standard depression labels demonstrate solid predictive performance, with embedding features, deep model architectures, and clinician ...

Abstract: Automatic text summarization has the aim to generate a concise version of a text while still preserving its main ideas, using an intelligent system. Developing an automatic text ...

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 ...

New NIH grant awards $2.5 million over 5 years for mechanistic study BURLINGTON, Mass. and JERUSALEM, Nov. 04, 2025 (GLOBE NEWSWIRE) -- BrainsWay Ltd. (NASDAQ & TASE: BWAY) (“BrainsWay” or the ...

Text Blaze is a digital tool designed to make life easier by saving time. While this was built for business, it's also tailored to use in education with a plan to save teachers on admin task time so ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

Automatic text summarization seeks to condense source documents into fluent, informative summaries that preserve essential meaning. Two principal approaches have emerged: extractive summarization, ...