IEEE

An Analysis of Semi-Supervised Machine Learning in Electrical Machines

Abstract: This research outlines the significance of semi-supervised machine learning (SSML) in dealing with the intricate characteristics of electrical machines. SSML provides a key benefit in ...

EPC Group Expands Power BI Copilot With Enterprise Multi-Model AI Architecture

New architecture integrates Copilot, Azure OpenAI, Claude, and Perplexity to transform Microsoft Power BI into an ...
Frontiers

Disease classification via interpretable machine learning based on multi-center routine coagulation test

Data from 11 hospitals were collected. An unsupervised clustering model was used to extract classification patterns, and clinical experts assigned disease labels. Multiple machine learning models, ...
IEEE

End-to-End Open-Set Semi-Supervised Learning for Fine-Grained Encrypted Traffic Classification

Abstract: Encrypted traffic classification is crucial for enhancing network management, service quality, and security. However, real-world network environments are inherently open-world scenarios in ...
The Lancet

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

aDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA bDepartment of Medicine, University of California Los Angeles, Los Angeles, CA, USA cDepartment of Medicine, ...