Machine learning: a new prospect in multi-omics data analysis of cancer
Cancer is defined as a large group of diseases that is associated with abnormal cell growth,
uncontrollable cell division, and may tend to impinge on other tissues of the body by different …
uncontrollable cell division, and may tend to impinge on other tissues of the body by different …
Machine learning for the advancement of membrane science and technology: A critical review
Abstract Machine learning (ML) has been rapidly transforming the landscape of natural
sciences and has the potential to revolutionize the process of data analysis and hypothesis …
sciences and has the potential to revolutionize the process of data analysis and hypothesis …
Robot-enabled construction assembly with automated sequence planning based on ChatGPT: RoboGPT
Robot-based assembly in construction has emerged as a promising solution to address
numerous challenges such as increasing costs, labor shortages, and the demand for safe …
numerous challenges such as increasing costs, labor shortages, and the demand for safe …
An ensemble learning based classification approach for the prediction of household solid waste generation
With the increase in urbanization and smart cities initiatives, the management of waste
generation has become a fundamental task. Recent studies have started applying machine …
generation has become a fundamental task. Recent studies have started applying machine …
Deep representation learning: Fundamentals, technologies, applications, and open challenges
Machine learning algorithms have had a profound impact on the field of computer science
over the past few decades. The performance of these algorithms heavily depends on the …
over the past few decades. The performance of these algorithms heavily depends on the …
Deep representation learning: Fundamentals, perspectives, applications, and open challenges
Machine Learning algorithms have had a profound impact on the field of computer science
over the past few decades. These algorithms performance is greatly influenced by the …
over the past few decades. These algorithms performance is greatly influenced by the …
Dataset quality assessment in autonomous networks with permutation testing
J Camacho, K Wasielewska - NOMS 2022-2022 IEEE/IFIP …, 2022 - ieeexplore.ieee.org
The development of autonomous or self-driving networks is one of the main challenges
faced by the telecommunication industry. Future networks are expected to realise a number …
faced by the telecommunication industry. Future networks are expected to realise a number …
[HTML][HTML] Exploring synergies between plant metabolic modelling and machine learning
As plants produce an enormous diversity of metabolites to help them adapt to the
environment, the study of plant metabolism is of utmost importance to understand different …
environment, the study of plant metabolism is of utmost importance to understand different …
Application of Neural Network Models with Ultra-Small Samples to Optimize the Ultrasonic Consolidation Parameters for 'PEI Adherend/Prepreg (CF-PEI Fabric)/PEI …
DY Stepanov, D Tian, VO Alexenko, SV Panin… - Polymers, 2024 - mdpi.com
The aim of this study was to optimize the ultrasonic consolidation (USC) parameters for 'PEI
adherend/Prepreg (CF-PEI fabric)/PEI adherend'lap joints. For this purpose, artificial neural …
adherend/Prepreg (CF-PEI fabric)/PEI adherend'lap joints. For this purpose, artificial neural …
Back to Normal? Harnessing Long Short-term Memory Network to Examine the Associations Between Adolescent Social Interactions and Depressive Symptoms …
Adolescence is a developmental period in which social interactions are critical for mental
health. While the onset of COVID-19 significantly disrupted adolescents' social environments …
health. While the onset of COVID-19 significantly disrupted adolescents' social environments …