News-Medical.Net

Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
Devdiscourse

Next-gen AI biosensors promise faster, smarter pandemic surveillance

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Devdiscourse

AI-driven air quality system promises faster, more reliable urban health warnings

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Ultra I&C leads live, all-digital kill chain demonstration with U.S. Marine Corps

Ultra I&C led a live, multi-company demonstration showcasing a fully digital sensor-to-effector kill chain, from threat detection to classification to engagement recommendation, powered by artificial ...
IEEE

MultiSenseNet: Multi-Modal Deep Learning for Machine Failure Risk Prediction

Abstract: Predictive maintenance plays a key role in industrial manufacturing by identifying machine failure risks early. This prevents downtime and improves efficiency, contributing towards industry ...

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 ...
usace.army.mil

Army establishes new AI, machine learning career path for officers

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...
Frontiers

Improved multi-scale divergence entropy combined with extreme learning machine classifier for rotating machinery fault recognition

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...