The Lancet

From prediction to navigation for artificial intelligence in medicine

Whether estimating the probability that a disease is present or forecasting risk of deterioration,1 readmission,2 or death,3 most contemporary clinical artificial intelligence (AI) systems are ...
Hosted on MSN

AI ensemble models sharpen NBA game predictions and strategy

New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...
Hosted on MSN

AI reshapes anime discovery with smarter, personalized tools

AI-powered anime recommendation systems are evolving from basic filters to sophisticated, context-aware tools that blend content analysis, collaborative filtering, and machine learning for highly ...
IEEE

Application of K-Nearest Neighbor Machine Learning Algorithm in High Voltage Circuit Breaker Monitoring System by Analyzing Spring Mechanism Motor Current

Abstract: Machine learning has been applied across various scientific fields and switching apparatus monitoring is no exception. Monitoring system is a crucial component of switching apparatus ...
Phys.org

Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Scientific Research Publishing

Larose, D.T. and Larose, C.D. (2014) k-Nearest Neighbor Algorithm.

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
Medscape

Machine Learning Algorithm Predicts Gout Flares Using RNA

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
Frontiers

Salp swarm-optimized machine learning models for predicting preoperative aortic rupture risk in acute type a aortic dissection patients

Acute Type A aortic dissection (ATAAD) is characterized by acute onset and rapid progression, with aortic rupture due to dissection extension being the primary lethal mechanism. Timely identification ...
IEEE

Machine Learning Based Prediction of Cardiovascular Disease Using KNN and SVM Algorithms

Abstract: Cardiovascular diseases are a significant reason of suffering and several healthy years of lives lost as well as deaths in the world at large. There is the possibility of significantly ...