A single sample classifier can predict cancer-associated fibroblast subtypes in patient samples

In a collaboration between several labs at UNC Lineberger, researchers have defined cancer-associated fibroblast (CAF) subtypes that are clinically robust, prognostic, and predictive of immunotherapy ...

AI-powered liquid biopsy can classify pediatric brain tumors with 92% accuracy

Liquid biopsies, which test body fluids that contain cancerous material, including circulating tumor DNA (ctDNA), are a ...
Ecommerce Fastlane

Best Amazon Marketing Agencies in Toronto for Sellers in 2026

Amazon's 2026 algorithm update prioritizes profitability signals, conversion quality, and AI-aligned content over traditional keyword stuffing. Agencies that ...
The Echo

University Professor’s New Book Encourages Curiosity In AI Era

California Lutheran University political science professor Jose Marichal discussed his new book, “You Must Become an Algorithmic Problem,” Thursday, Feb. 12, in Ullman 101. The book, Marichal’s second ...
IEEE

Performance of Classification Algorithms Under Class Imbalance: Simulation and Real-World Evidence

Abstract: Class imbalance is a persistent challenge in machine learning, particularly in high-stakes applications such as medical diagnostics, bioinformatics, and fraud detection, where the minority ...
IEEE

Classification Algorithms in Automatic Diagnosis of ECG Arrhythmias: A Review

Abstract: ECG (Electrocardiogram), the most commonly used tool in the diagnosis of cardiac diseases, contains a large amount of physiologic information about the electrical activity of the heart.
Frontiers

Medical pattern classification using a novel binary similarity approach based on an associative classifier

Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning ...
Scientific Research Publishing

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Seeking Alpha

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (MLGO) (the "Company" or "MicroAlgo") announced today the launch of their latest classifier auto-optimization technology based on ...
Scientific Research Publishing

Lessmann, S., et al. (2015) Benchmarking State-of-the-Art Classification Algorithms for Credit Scoring. Journal of the Operational Research Society, 66, 743-755.

ABSTRACT: This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based ...