Emerging AI technologies for corrosion monitoring in oil and gas industry: A comprehensive review

AH Khalaf, Y **ao, N Xu, B Wu, H Li, B Lin, Z Nie… - Engineering Failure …, 2024 - Elsevier
Corrosion presents a daunting challenge to the oil and gas industry, resulting in substantial
maintenance expenses and productivity losses. Conventional corrosion monitoring …

Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods

X Zhang, L Yu - Expert Systems with Applications, 2024 - Elsevier
Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …

Myocardial infarction detection based on deep neural network on imbalanced data

M Hammad, MH Alkinani, BB Gupta, AA Abd El-Latif - Multimedia Systems, 2022 - Springer
Myocardial infarction (MI) is an acute interruption of blood flow to the heart, which causes the
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …

A study on arrhythmia via ECG signal classification using the convolutional neural network

M Wu, Y Lu, W Yang, SY Wong - Frontiers in computational …, 2021 - frontiersin.org
Cardiovascular diseases (CVDs) are the leading cause of death today. The current
identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a …

Three and a half decades of artificial intelligence in banking, financial services, and insurance: A systematic evolutionary review

H Herrmann, B Masawi - Strategic Change, 2022 - Wiley Online Library
The banking, financial services, and insurance (BFSI) sector is one of the earliest and most
prominent adopters of artificial intelligence (AI). However, academic research substantially …

Identifying crop diseases using attention embedded MobileNet-V2 model

J Chen, D Zhang, M Suzauddola, A Zeb - Applied Soft Computing, 2021 - Elsevier
Various crop diseases are a major problem worldwide since their occurrence leads to a
significant decrease in crop production. The image-based automatic identification of crop …

A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques

ME Basiri, M Abdar, MA Cifci, S Nemati… - Knowledge-Based …, 2020 - Elsevier
Nowadays, the development of new computer-based technologies has led to rapid increase
in the volume of user-generated textual content on the website. Patient-written medical and …

An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices

AF Kamara, E Chen, Z Pan - Information Sciences, 2022 - Elsevier
For several years the modeling as well as forecasting of the prices of stocks have been
extremely challenging for the business community and researchers as a result of the …

The fusion of deep learning and fuzzy systems: A state-of-the-art survey

Y Zheng, Z Xu, X Wang - IEEE Transactions on Fuzzy Systems, 2021 - ieeexplore.ieee.org
Deep learning presents excellent learning ability in constructing learning model and greatly
promotes the development of artificial intelligence, but its conventional models cannot …

[HTML][HTML] Credit scoring methods: Latest trends and points to consider

A Markov, Z Seleznyova, V Lapshin - The Journal of Finance and Data …, 2022 - Elsevier
Credit risk is the most significant risk by impact for any bank and financial institution.
Accurate credit risk assessment affects an organisation's balance sheet and income …