scholarly journals Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging

2020 ◽  
Vol 60 (1) ◽  
Author(s):  
Matheus Calil Faleiros ◽  
Marcello Henrique Nogueira-Barbosa ◽  
Vitor Faeda Dalto ◽  
José Raniery Ferreira Júnior ◽  
Ariane Priscilla Magalhães Tenório ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Machine Learning ◽  
Magnetic Resonance ◽  
Machine Learning Techniques ◽  
Resonance Imaging ◽  
Learning Techniques ◽  
Computer Aided

scholarly journals Analysis of Machine Learning Techniques Applied to the Classification of Masses and Microcalcification Clusters in Breast Cancer Computer-Aided Detection

2012 ◽  
Vol 03 (06) ◽  
pp. 1020-1028 ◽  
Author(s):  
Edén A. Alanís-Reyes ◽  
José L. Hernández-Cruz ◽  
Jesús S. Cepeda ◽  
Camila Castro ◽  
Hugo Terashima-Marín ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Machine Learning Techniques ◽  
Computer Aided Detection ◽  
Learning Techniques ◽  
Computer Aided ◽  
Microcalcification Clusters

scholarly journals Brain Tissue Classification to Detect Focal Cortical Dysplasia in Magnetic Resonance Imaging

2020 ◽  
Author(s):  
Fabricio Simozo ◽  
Marcos Oliveira ◽  
Luiz Murta-Junior
Keyword(s):  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Refractory Epilepsy ◽  
Focal Cortical Dysplasia ◽  
Cortical Dysplasia ◽  
Machine Learning Techniques ◽  
Resonance Imaging ◽  
Learning Techniques ◽  
Common Causes

Focal cortical dysplasia (FCD) is a local malformation of the cortex, the main cause of refractory epilepsy in childhood and one of the most common causes in adults. The surgery decision and planning depend on the FCD localization. Although recent studies have successfully detected FCD through artificial intelligence, no study investigates the relevance and prevalence of cortical features on FCD identification and the performance of different machine learning techniques. In this study, the proposed method constructed a voxel-based set of features, e.g., texture measure, border definition, cortical thickness.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

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