IEEE

LYRICEL: Knowledge Graphs Combined With Large Language Models and Machine Learning for Cross-Cultural Analysis of Lyrics—The Case of Greek Songs

Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...
IEEE

Rainfall Prediction Using Integrated Machine Learning Models With K-Means Clustering: A Representative Case Study of Harirud Murghab Basin-Afghanistan

Abstract: Accurate rainfall prediction was essential for effective water resource management and disaster preparedness, especially in regions with limited observational data such as Afghanistan. This ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
C&EN

PHYSPROPNET: A Benchmarking Study of Machine Learning Models for Physicochemical Property Prediction in Data-Limited Environmental Research

Machine learning is increasingly applied in environmental chemistry for contaminant screening and property prediction, yet consistent benchmarks are lacking. We compared eight graph neural networks ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
hospitalhealthcare

Can machine learning identify CAD risk and refine patient selection in CCTA?

While machine learning can sharpen coronary artery disease (CAD) prediction using standard clinical data, it falls short in detecting plaques most likely to cause future cardiac events in patients ...
ahajournals.org

Abstract 4357549: Multi-Center Validation of a Non-exercise Machine Learning Prediction Model Equivalent to Cardiopulmonary Exercise Parameters in Cardiovascular Patients

Background: A symptom-limited incremental cardiopulmonary exercise testing (CPET) is rigidly applied to patients with cardiovascular disease for assessing exercise capacity and prognosis, yet its ...
VentureBeat

Large reasoning models almost certainly can think

Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of ...
C&EN

A Comprehensive Machine Learning Model for Metal–Ligand Binding Prediction: Applications in Chemistry and Biology

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
Time

AI Is Learning to Predict the Future—And Beating Humans at It

Reactions to Kimmel's suspension, Trump publicly rebukes Putin, and more Length: Long Speed: 1.0x Every three months, participants in the Metaculus forecasting cup try to predict the future for a ...