Neural decoding of EEG signals with machine learning: a systematic review

M Saeidi, W Karwowski, FV Farahani, K Fiok, R Taiar… - Brain Sciences, 2021 - mdpi.com
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

Quantum machine learning for chemistry and physics

M Sajjan, J Li, R Selvarajan, SH Sureshbabu… - Chemical Society …, 2022 - pubs.rsc.org
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …

“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model

D Menon, K Shilpa - Heliyon, 2023 - cell.com
Open AI's ChatGPT has emerged as a popular AI language model that can engage in
natural language conversations with users. Based on a qualitative research approach using …

Deploying machine and deep learning models for efficient data-augmented detection of COVID-19 infections

A Sedik, AM Iliyasu, B Abd El-Rahiem… - Viruses, 2020 - mdpi.com
This generation faces existential threats because of the global assault of the novel Corona
virus 2019 (ie, COVID-19). With more than thirteen million infected and nearly 600000 …

Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review

GA Mesías-Ruiz, M Pérez-Ortiz, J Dorado… - Frontiers in Plant …, 2023 - frontiersin.org
Crop protection is a key activity for the sustainability and feasibility of agriculture in a current
context of climate change, which is causing the destabilization of agricultural practices and …

A novel architecture for web-based attack detection using convolutional neural network

A Tekerek - Computers & Security, 2021 - Elsevier
Unprotected Web applications are vulnerable places for hackers to attack an organization's
network. Statistics show that 42% of Web applications are exposed to threats and hackers …

[HTML][HTML] Machine learning techniques for sequence-based prediction of viral–host interactions between SARS-CoV-2 and human proteins

L Dey, S Chakraborty, A Mukhopadhyay - Biomedical journal, 2020 - Elsevier
Abstract Background COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-
CoV-2 virus, has been declared as a pandemic by the World Health Organization on March …

Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

AM Al-Abdullatif, AA Al-Dokhny, AM Drwish - Frontiers in Psychology, 2023 - frontiersin.org
Since the fourth industrial revolution, intelligent software and applications that attempt to
mimic human behavior have become increasingly common. The chatbot is an example of an …

A comprehensive survey on the progress, process, and challenges of lung cancer detection and classification

MF Mridha, AR Prodeep, ASMM Hoque… - Journal of …, 2022 - Wiley Online Library
Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death
rate is increasing step by step. There are chances of recovering from lung cancer by …

A comparative analysis of converters of tabular data into image for the classification of Arboviruses using Convolutional Neural Networks

L Medeiros Neto, S Rogerio da Silva Neto, PT Endo - Plos one, 2023 - journals.plos.org
Tabular data is commonly used in business and literature and can be analyzed using tree-
based Machine Learning (ML) algorithms to extract meaningful information. Deep Learning …