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 ...

AI-powered document processing automates data extraction, classification, and validation with 95-99% accuracyMarket projected ...

The agency’s 31% year-over-year surge in AI use cases includes work with predictive models and surveillance technologies that ...

Researchers reveal Prototaxites, a giant Devonian fossil, was not a fungus or plant but a unique extinct lineage.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

In order to explore the medication rules of Shang Han Lun, this article conducted complex network analysis and cluster analysis on the 112 prescriptions in Shang Han Lun. Statistical and network ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...

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

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.

Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...

Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...