scholarly journals Fragments‐Expert: A graphical user interface MATLAB toolbox for classification of file fragments

2020 ◽  
Author(s):  
Mehdi Teimouri ◽  
Zahra Seyedghorban ◽  
Fatemeh Amirjani
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Matlab Toolbox

scholarly journals HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0246039
Author(s):  
Shilan S. Hameed ◽  
Rohayanti Hassan ◽  
Wan Haslina Hassan ◽  
Fahmi F. Muhammadsharif ◽  
Liza Abdul Latiff
Keyword(s):  
Machine Learning ◽  
User Interface ◽  
Graphical User Interface ◽  
Efficient Algorithm ◽  
Gene Selection ◽  
High Dimensional ◽  
Competitive Performance ◽  
User Friendly ◽  
High Dimensional Datasets

The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.

scholarly journals An Automated Detection of Leukemia

2021 ◽  
Vol 9 (8) ◽  
pp. 1977-1981
Author(s):  
Ajay Rajaraman
Keyword(s):  
Image Processing ◽  
User Interface ◽  
Random Forest ◽  
Graphical User Interface ◽  
Blood Cells ◽  
Visual Inspection ◽  
Automated Detection ◽  
Blood Disorders ◽  
Preliminary Study

Abstract: Currently, the identification of blood disorders is through visual inspection of microscopic images of the blood cells. The identification of blood disorders can lead to the classification of certain diseases related to blood. This paper describes a preliminary study of developing the detection of leukemia types using microscopic blood sample images. Analyzing through images is very important because diseases can be detected and diagnosed at an earlier stage. From there further actions like controlling, monitoring, and prevention of diseases can be done. Keywords: Image processing; leukemia detection; Lymphocytes; Myelocytes; Random Forest; Graphical User Interface.

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