Traditional machine learning in banking requires 3–4 months per use case: feature engineering, data labeling, model training, validation, deployment. Zero-shot inference on knowledge graphs eliminates ...

The mission of the GO Consortium is to develop a comprehensive, computational model of biological systems, ranging from the molecular to the organism level, across the multiplicity of species in the ...

Objectives Non-alcoholic fatty liver disease (NAFLD) is a non-communicable disease with a rising prevalence worldwide and with large burden for patients and health systems. To date, the presence of ...

Launch ontology-driven agentic AI platform to modernize telecom and enterprise data management. Utilize Microsoft Fabric and Azure AI for explainable, real-time AI-powered decision-making. Tech ...

In his provocative X article, Matt Shumer, CEO of HyperWrite and OthersideAI, declares, "Every time someone asks me what's going on with AI, I give them the safe answer. Because the real one sounds ...

One of Python’s most persistent limitations is how unnecessarily difficult it is to take a Python program and give it to another user as a self-contained click-to-run package. The design of the Python ...

Free-threaded Python is now officially supported, though using it remains optional. Here are four tips for developers getting started with true parallelism in Python. Until recently, Python threads ...

OntoLearner is a modular and extensible Python library for ontology learning powered by Large Language Models (LLMs). It provides a unified framework covering the full workflow — from loading and ...

Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are a critical part of such analyses. Cardiac ultrasound reports include structured and free text and ...

Cyber situational awareness is critical for detecting and mitigating cybersecurity threats in real-time. This study introduces a comprehensive methodology that integrates the Isolation Forest and ...

ABSTRACT: With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with ...