Concepts of artificial intelligence for computer-assisted drug discovery

X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

A Complete Process of Text Classification System Using State‐of‐the‐Art NLP Models

V Dogra, S Verma, Kavita, P Chatterjee… - Computational …, 2022 - Wiley Online Library
With the rapid advancement of information technology, online information has been
exponentially growing day by day, especially in the form of text documents such as news …

A data-driven approach for intrusion and anomaly detection using automated machine learning for the Internet of Things

H Xu, Z Sun, Y Cao, H Bilal - Soft Computing, 2023 - Springer
Cyber-attacks and network intrusion have surfaced as major concerns for modern days
applications of the Internet of Things (IoT). The existing intrusion detection and prevention …

Investigating the impact of data normalization on classification performance

D Singh, B Singh - Applied Soft Computing, 2020 - Elsevier
Data normalization is one of the pre-processing approaches where the data is either scaled
or transformed to make an equal contribution of each feature. The success of machine …

[HTML][HTML] Metabolomics of exhaled breath in critically ill COVID-19 patients: A pilot study

S Grassin-Delyle, C Roquencourt, P Moine, G Saffroy… - …, 2021 - thelancet.com
Background Early diagnosis of coronavirus disease 2019 (COVID-19) is of the utmost
importance but remains challenging. The objective of the current study was to characterize …

[HTML][HTML] A review of supervised object-based land-cover image classification

L Ma, M Li, X Ma, L Cheng, P Du, Y Liu - ISPRS Journal of Photogrammetry …, 2017 - Elsevier
Object-based image classification for land-cover mapping purposes using remote-sensing
imagery has attracted significant attention in recent years. Numerous studies conducted over …

[HTML][HTML] SVM-RFE: selection and visualization of the most relevant features through non-linear kernels

H Sanz, C Valim, E Vegas, JM Oller, F Reverter - BMC bioinformatics, 2018 - Springer
Background Support vector machines (SVM) are a powerful tool to analyze data with a
number of predictors approximately equal or larger than the number of observations …

[HTML][HTML] Prediction of type 2 diabetes based on machine learning algorithm

HM Deberneh, I Kim - International journal of environmental research and …, 2021 - mdpi.com
Prediction of type 2 diabetes (T2D) occurrence allows a person at risk to take actions that
can prevent onset or delay the progression of the disease. In this study, we developed a …

Feature selection for text classification: A review

X Deng, Y Li, J Weng, J Zhang - Multimedia Tools and Applications, 2019 - Springer
Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …

Survey on SVM and their application in image classification

MA Chandra, SS Bedi - International Journal of Information Technology, 2021 - Springer
Life of any living being is impossible if it does not have the ability to differentiate between
various things, objects, smell, taste, colors, etc. Human being is a good ability to classify the …