[HTML][HTML] A systematic literature review and future perspectives for handling big data analytics in COVID-19 diagnosis

N Tenali, GRM Babu - New Generation Computing, 2023 - Springer
In today's digital world, information is growing along with the expansion of Internet usage
worldwide. As a consequence, bulk of data is generated constantly which is known to be …

[HTML][HTML] A systematic review of literature on credit card cyber fraud detection using machine and deep learning

EALM Btoush, X Zhou, R Gururajan, KC Chan… - PeerJ Computer …, 2023 - peerj.com
The increasing spread of cyberattacks and crimes makes cyber security a top priority in the
banking industry. Credit card cyber fraud is a major security risk worldwide. Conventional …

A novel Random Forest integrated model for imbalanced data classification problem

Q Gu, J Tian, X Li, S Jiang - Knowledge-Based Systems, 2022 - Elsevier
In recent years, most researchers focused on the classification problems of imbalanced data
sets, and these problems are widely distributed in industrial production and medical …

Stroke disease prediction based on ECG signals using deep learning techniques

MA Kumar, N Abirami, MSG Prasad… - 2022 International …, 2022 - ieeexplore.ieee.org
Stroke-related diseases are rapidly increasing day by day due to the changes in
environmental factors including lifestyles, food habits, and stress-related working cultures …

[HTML][HTML] A soft voting ensemble learning approach for credit card fraud detection

MA Mim, N Majadi, P Mazumder - Heliyon, 2024 - cell.com
With the advancement of e-commerce and modern technological development, credit cards
are widely used for both online and offline purchases, which has increased the number of …

Credit Card Fraud Detection Based on Hyperparameters‎ Optimization Using the Differential Evolution

M Tayebi, S El Kafhali - … Journal of Information Security and Privacy …, 2022 - igi-global.com
Due to the emigration of world business to the internet, credit‎ cards have become a tool for‎
payments for both online and outline purchases. However, fraudsters try‎ to attack those …

A body area network approach for stroke-related disease diagnosis using artificial intelligence with deep learning techniques

MA Kumar, AS Kumar - … conference on advances in computing and data …, 2022 - Springer
Stroke is the second largest disease after heart disease that leads to death. Stroke-related
diseases need immediate attention from health care experts. With rapid growth and …

A voting ensemble machine learning based credit card fraud detection using highly imbalance data

R Chhabra, S Goswami, RK Ranjan - Multimedia Tools and Applications, 2023 - Springer
Long gone is the time when people preferred using only cash. In recent years, cashless
transactions have gained much popularity, be it using UPI apps or credit and debit cards …

A clustering-based adaptive undersampling ensemble method for highly unbalanced data classification

X Yuan, C Sun, S Chen - Applied Soft Computing, 2024 - Elsevier
The class imbalance issue is prevalent in various practical classification tasks. A high
unbalanced rate will significantly decrease the classification performance of unbalanced …

A Hybrid Approach Adopted for Credit Card Fraud Detection Based on Deep Neural Networks and Attention Mechanism

VC Maheshwari, NA Osman… - Journal of Advanced …, 2023 - semarakilmu.com.my
Over the past few years, credit card fraud has become a serious problem as more
individuals rely on credit cards for purchases. The significant increase in fraudulent activities …