YouTube’s recommendation engine failed on February 17, 2026, stranding hundreds of thousands of users on blank, unresponsive ...

Researchers identified a gene niche that promotes liver tumorigenesis and built a machine-learning score to detect it. The model predicted cancer risk and recurrence with high accuracy using non-tumor ...

Researchers at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. The ...

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...

The Indian Medical Council has launched a new pathogen detection tool. An AI-driven tool could predict the spread of serious diseases, and here is what you should know.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

This study aimed to develop a machine learning–based model to predict recurrence risk after perianal abscess surgery, thereby supporting personalized follow-up and intervention strategies. Clinical ...

Association between prostate specific membrane antigen imaging and initial treatment for prostate cancer among commercial insurance beneficiaries. This is an ASCO Meeting Abstract from the 2025 ASCO ...

A common over-the-counter medication could significantly reduce the risk of colorectal cancer coming back. In a Swedish study, a low dose of aspirin was shown to slash recurrence in half for patients ...

Function-as-a-Service (FaaS) introduces a lightweight, function-based cloud execution model that finds its relevance in a range of applications like IoT-edge data processing and anomaly detection.

Abstract: This paper introduces a novel method based on symmetric cryptography relying on Appell's recurrent hypergeometric functions of two variables. The implementation was done in C# and our method ...