Machine learning for big data analytics in plants
Rapid advances in high-throughput genomic technology have enabled biology to enter the
era of 'Big Data'(large datasets). The plant science community not only needs to build its …
era of 'Big Data'(large datasets). The plant science community not only needs to build its …
Predicting novel microRNA: a comprehensive comparison of machine learning approaches
Motivation The importance of microRNAs (miRNAs) is widely recognized in the community
nowadays because these short segments of RNA can play several roles in almost all …
nowadays because these short segments of RNA can play several roles in almost all …
Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs
T Fehlmann, C Backes, M Kahraman… - Nucleic acids …, 2017 - academic.oup.com
The analysis of small RNA NGS data together with the discovery of new small RNAs is
among the foremost challenges in life science. For the analysis of raw high-throughput …
among the foremost challenges in life science. For the analysis of raw high-throughput …
Imbalance learning using heterogeneous ensembles
HG Zefrehi, H Altınçay - Expert Systems with Applications, 2020 - Elsevier
In binary classification, class-imbalance problem occurs when the number of samples in one
class is much larger than that of the other class. In such cases, the performance of a …
class is much larger than that of the other class. In such cases, the performance of a …
Efficient bladder cancer diagnosis using an improved RIME algorithm with Orthogonal Learning
Bladder cancer (BC) diagnosis presents a critical challenge in biomedical research,
necessitating accurate tumor classification from diverse datasets for effective treatment …
necessitating accurate tumor classification from diverse datasets for effective treatment …
GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides
Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA)
sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is …
sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is …
HBoost: A heterogeneous ensemble classifier based on the Boosting method and entropy measurement
HR Kadkhodaei, AME Moghadam… - Expert Systems with …, 2020 - Elsevier
In recent years, ensemble classifiers have attracted a lot of attention in the field of machine
learning. The main challenges with these classifiers are 1) to select the base classifiers and …
learning. The main challenges with these classifiers are 1) to select the base classifiers and …
Identifying maximum imbalance in datasets for fault diagnosis of gearboxes
P Santos, J Maudes, A Bustillo - Journal of Intelligent Manufacturing, 2018 - Springer
Research into fault diagnosis in rotating machinery with a wide range of variable loads and
speeds, such as the gearboxes of wind turbines, is of great industrial interest. Although …
speeds, such as the gearboxes of wind turbines, is of great industrial interest. Although …
Predicting prolonged length of ICU stay through machine learning
This study aimed to construct machine learning (ML) models for predicting prolonged length
of stay (pLOS) in intensive care units (ICU) among general ICU patients. A multicenter …
of stay (pLOS) in intensive care units (ICU) among general ICU patients. A multicenter …
Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order derivative maps
X Xu, Y Liu, X Zhang, Q Tian, Y Wu, G Zhang… - Abdominal …, 2017 - Springer
Purpose To determine radiomic features which are capable of reflecting muscular
invasiveness of bladder cancer (BC) and propose a non-invasive strategy for the …
invasiveness of bladder cancer (BC) and propose a non-invasive strategy for the …