Artificial intelligence in surveillance, diagnosis, drug discovery and vaccine development against COVID-19
As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-
confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic …
confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic …
Review of feature selection approaches based on grouping of features
With the rapid development in technology, large amounts of high-dimensional data have
been generated. This high dimensionality including redundancy and irrelevancy poses a …
been generated. This high dimensionality including redundancy and irrelevancy poses a …
Ensemble feature selection for multi‐label text classification: An intelligent order statistics approach
M Miri, MB Dowlatshahi, A Hashemi… - … Journal of Intelligent …, 2022 - Wiley Online Library
Because of the overgrowth of data, especially in text format, the value and importance of
multi‐label text classification have increased. Aside from this, preprocessing and particularly …
multi‐label text classification have increased. Aside from this, preprocessing and particularly …
Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods
The tremendous boost in next generation sequencing and in the “omics” technologies
makes it possible to characterize the human gut microbiome—the collective genomes of the …
makes it possible to characterize the human gut microbiome—the collective genomes of the …
GediNET for discovering gene associations across diseases using knowledge based machine learning approach
The most common approaches to discovering genes associated with specific diseases are
based on machine learning and use a variety of feature selection techniques to identify …
based on machine learning and use a variety of feature selection techniques to identify …
TextNetTopics: text classification based word grouping as topics and topics' scoring
M Yousef, D Voskergian - Frontiers in Genetics, 2022 - frontiersin.org
Medical document classification is one of the active research problems and the most
challenging within the text classification domain. Medical datasets often contain massive …
challenging within the text classification domain. Medical datasets often contain massive …
A review on recent progress in machine learning and deep learning methods for cancer classification on gene expression data
Data-driven model with predictive ability are important to be used in medical and healthcare.
However, the most challenging task in predictive modeling is to construct a prediction model …
However, the most challenging task in predictive modeling is to construct a prediction model …
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
Background Cell homeostasis relies on the concerted actions of genes, and dysregulated
genes can lead to diseases. In living organisms, genes or their products do not act alone but …
genes can lead to diseases. In living organisms, genes or their products do not act alone but …
Prediction of linear cationic antimicrobial peptides active against gram-negative and gram-positive bacteria based on machine learning models
Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional
antibiotics in order to overcome the growing problems of antibiotic resistance …
antibiotics in order to overcome the growing problems of antibiotic resistance …
miRdisNET: discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
During recent years, biological experiments and increasing evidence have shown that
microRNAs play an important role in the diagnosis and treatment of human complex …
microRNAs play an important role in the diagnosis and treatment of human complex …