GBM detected additional 24 and nine signals for nivolumab and 82 and 76 for docetaxel compared to ROR and IC, respectively, from the unknown ADR datasets. Conclusion: Machine learning algorithm based ...

Machine learning enables computers to learn from data and make judgments without requiring explicit programming using a number of key steps from data collection to model deployment.

Main outcomes/measures Data of patients with ADR who used Chinese herbal injections containing Panax notoginseng saponin were collected from the National Center for ADR Monitoring. A nested ...

Whether trained via supervised or unsupervised learning, the advantage of deploying these solutions for anomaly detection is that they don’t require pre-compiled sets of rules and are very adaptive, ...

Considering seemingly minor tampering can be catastrophic, proactive detection efforts are essential. Ways to detect a poisoned machine learning dataset ...

This study addresses the data characteristics and practical needs of industrial equipment fault diagnosis by leveraging real-world data to develop and evaluate machine learning models for fault ...

The study uses meteorological data collected over 40 years (1981-2021) from ten synoptic stations operated by Burkina Faso’s National Meteorological Agency (ANAM). The methodology is based on the use ...

Researchers are applying machine learning algorithms to help interpret massive amounts of ground deformation data collected with Interferometric Synthetic Aperture Radar (InSAR) satellites; the ...