The use of machine learning and deep learning algorithms in functional magnetic resonance imaging—A systematic review
Abstract Functional Magnetic Resonance Imaging (fMRI) is presently one of the most
popular techniques for analysing the dynamic states in brain images using various kinds of …
popular techniques for analysing the dynamic states in brain images using various kinds of …
Protein deep profile and model predictions for identifying the causal genes of male infertility based on deep learning
F Xu, G Guo, F Zhu, X Tan, L Fan - Information Fusion, 2021 - Elsevier
A principal task in dissecting the genetics of complex traits is to identify causal genes for
disease phenotypes. Millions of genes have been sequenced in data-driven genomics era …
disease phenotypes. Millions of genes have been sequenced in data-driven genomics era …
Alpha skew gaussian naïve bayes classifier
The main goal of this paper is to introduce a new procedure for a naïve Bayes classifier,
namely alpha skew Gaussian naïve Bayes (ASGNB), which is based on a flexible …
namely alpha skew Gaussian naïve Bayes (ASGNB), which is based on a flexible …
Classification of cognitive state using clustering based maximum margin feature selection framework
JS Ramakrishna, H Ramasangu - … International Conference on …, 2017 - ieeexplore.ieee.org
Over the past few years, the dimensionality of functional MRI (fMRI) effects the analysis of
brain data. In the field of machine learning and statistical analysis, classification of objects …
brain data. In the field of machine learning and statistical analysis, classification of objects …
Classification of cognitive state using statistics of split time series
JS Ramakrishna, H Ramasangu - 2016 IEEE Annual India …, 2016 - ieeexplore.ieee.org
Functional MRI (fMRI) data comprises of a set of trials, each trial is described in terms of a
group of 20 to 25 anatomical Region Of Interests (ROI). Each ROI consists of neuroimage …
group of 20 to 25 anatomical Region Of Interests (ROI). Each ROI consists of neuroimage …
Cognitive state classification using clustering-classifier hybrid method
JS Ramakrishna, H Ramasangu - … International Conference on …, 2016 - ieeexplore.ieee.org
Classification is a familiar technique used to classify objects. Clustering techniques are
employed to segment data into multiple groups. Objects present in clusters exhibit similar …
employed to segment data into multiple groups. Objects present in clusters exhibit similar …
Analysis of the impact of online education using EEG signals and machine learning algorithms
E Hoque, T Ahmed, MA Shabab, TM Bakhtier… - 2021 - dspace.bracu.ac.bd
Online learning has allowed students from different walks of life to access a vast amount of
information, allowing them to gain new skills. However, only having access to that …
information, allowing them to gain new skills. However, only having access to that …
Estimation of transition temperature for doped iron-based superconductors based on crystal cell structure
H Zhang, Y Zhang, Y Zhu, Y Xu, W Shen… - 2015 11th …, 2015 - ieeexplore.ieee.org
From the experimental dataset on the superconducting transition temperatures Tc for 31
different superconductors of the doping iron-based oxy-arsenide systems, rough set theory …
different superconductors of the doping iron-based oxy-arsenide systems, rough set theory …