scholarly journals Machine Learning Methods for Prediction of Food Effects on Bioavailability: A Comparison of Support Vector Machines and Artificial Neural Networks

2021 ◽  
pp. 106018
Author(s):  
Harriet Bennett-Lenane ◽  
Brendan T. Griffin ◽  
Joseph P. O'Shea
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Support Vector Machines ◽  
Support Vector ◽  
Food Effects ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Vector Machines ◽  
Artificial Neural

scholarly journals Advanced machine learning methods in psychiatry: an introduction

2020 ◽  
Vol 33 (2) ◽  
pp. e100197 ◽  
Author(s):  
Tsung-Chin Wu ◽  
Zhirou Zhou ◽  
Hongyue Wang ◽  
Bokai Wang ◽  
Tuo Lin ◽  
...  
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Support Vector Machines ◽  
Support Vector ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Vector Machines ◽  
Artificial Neural

Mental health questions can be tackled through machine learning (ML) techniques. Apart from the two ML methods we introduced in our previous paper, we discuss two more advanced ML approaches in this paper: support vector machines and artificial neural networks. To illustrate how these ML methods have been employed in mental health, recent research applications in psychiatry were reported.

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