Machine learning based computational gene selection models: a survey, performance evaluation, open issues, and future research directions

N Mahendran, PM Durai Raj Vincent… - Frontiers in …, 2020 - frontiersin.org
Gene Expression is the process of determining the physical characteristics of living beings
by generating the necessary proteins. Gene Expression takes place in two steps, translation …

[HTML][HTML] Support vector machine-based differentiation between aggressive and chronic periodontitis using microbial profiles

M Feres, Y Louzoun, S Haber, M Faveri… - International dental …, 2018 - Elsevier
Background: The existence of specific microbial profiles for different periodontal conditions
is still a matter of debate. The aim of this study was to test the hypothesis that 40 bacterial …

Prediction of chronic periodontitis severity using machine learning models based on salivary bacterial copy number

EH Kim, S Kim, HJ Kim, H Jeong, J Lee… - Frontiers in Cellular …, 2020 - frontiersin.org
Periodontitis is a widespread chronic inflammatory disease caused by interactions between
periodontal bacteria and homeostasis in the host. We aimed to investigate the performance …

Generative artificial intelligence: fundamentals

JM Corchado, S López, R Garcia… - ADCAIJ: advances in …, 2023 - revistas.usal.es
Generative language models have witnessed substantial traction, notably with the
introduction of refined models aimed at more coherent user-AI interactions—principally …

A novel deep flexible neural forest model for classification of cancer subtypes based on gene expression data

J Xu, P Wu, Y Chen, Q Meng, H Dawood… - IEEE Access, 2019 - ieeexplore.ieee.org
Classification of cancer subtypes is of paramount importance for diagnosis and prognosis of
cancer. In recent years, deep learning methods have gained considerable popularity for …

Incorporating pathway information into feature selection towards better performed gene signatures

S Tian, C Wang, B Wang - BioMed research international, 2019 - Wiley Online Library
To analyze gene expression data with sophisticated grouping structures and to extract
hidden patterns from such data, feature selection is of critical importance. It is well known …

A CBR framework with gradient boosting based feature selection for lung cancer subtype classification

J Ramos-González, D López-Sánchez… - Computers in biology …, 2017 - Elsevier
Molecular subtype classification represents a challenging field in lung cancer diagnosis.
Although different methods have been proposed for biomarker selection, efficient …

Development and validation of a gene signature classifier for consensus molecular subtyping of colorectal carcinoma in a CLIA-certified setting

JS Morris, R Luthra, Y Liu, DY Duose, W Lee… - Clinical Cancer …, 2021 - AACR
Purpose: Consensus molecular subtyping (CMS) of colorectal cancer has potential to
reshape the colorectal cancer landscape. We developed and validated an assay that is …

A novel molecular descriptor selection method in QSAR classification model based on weighted penalized logistic regression

ZY Algamal, MH Lee - Journal of Chemometrics, 2017 - Wiley Online Library
Molecular descriptor selection is a pivotal tool for quantitative structure–activity relationship
modeling. This paper proposes a novel molecular descriptor selection method on the basis …

Feature selection from microarray data based on deep learning approach

N Bhui, PK Ram, P Kuila - 2020 11th International Conference …, 2020 - ieeexplore.ieee.org
In the field of medical care, feature (gene) selection has been a chronic research topic. For
the feature selection, microarray data are an exigent part to diagnose any disease. In any …