Fentanyl or phony? Machine learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Conventus Law

India – Medical Device As Software: Has CDSCO Guidance Changed The Rules?

Has CDSCO Guidance Changed The Rules? Legal News and Analysis - India - Regulatory & Compliance - Conventus Law ...
Medical Xpress

Information Science: News and Research on Classification Algorithms

Cancer is one of the most devastating diseases in the world. In 2023, more than 1.9 million new cancer cases and 609,820 deaths are projected to occur in the United States alone. As efforts are ...
Bulletin of the Atomic Scientists

Division begets division in the age of algorithmic classification

Social media and algorithmic recommendations aren’t just reflecting our divisions — they’re driving them. According to a poll conducted by Siena University and The New York Times, “most voters think ...
Frontiers

Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field

Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...
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 ...
IEEE

Dynamic Classification: Leveraging Self-Supervised Classification to Enhance Prediction Performance

Abstract: In this study, we propose an innovative dynamic classification algorithm aimed at achieving zero missed detections and minimal false positives, critical in safety-critical domains (e.g., ...