Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

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

Quiq reports on the role of automation in customer service, highlighting tools like AI for questions, ticket classification, and enhancing user experiences.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Breast cancer remains a critical global health challenge, representing one of the most prevalent and life-threatening malignancies affecting women worldwide. Traditional diagnostic approaches, while ...

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...

The paper is devoted to the optimization of data structure in classification and clustering problems by mapping the original data onto a set of ordered feature vectors. When ordering, the elements of ...

MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Key Laboratory of Pathogen Bioscience and Anti-Infective Medicine, Department of Bioinformatics and Computational Biology, School of ...

Traditional classification models, such as logistic regression, have a limited ability to predict the enrollment of households to CBHI. Therefore, employing machine learning models for predicting CBHI ...