Lessons learned from the application of machine learning to studies on plant response to radio-frequency tech./dosim.

Exposure

• • RF field

Related articles

• Halgamuge MN (2020): Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells
• Halgamuge MN (2017): Machine Learning for Bioelectromagnetics: Prediction Model using Data of Weak Radiofrequency Radiation Effect on Plants