AIMC Topic: Fraud

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Detection of Ponzi scheme on Ethereum using machine learning algorithms.

Scientific reports Oct 27, 2023
Security threats posed by Ponzi schemes present a considerably higher risk compared to many other online crimes. These fraudulent online businesses, including Ponzi schemes, have witnessed rapid growth and emerged as major threats in societies like N...
Humans Neural Networks, Computer Random Forest Fraud Algorithms Machine Learning
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Procedure code overutilization detection from healthcare claims using unsupervised deep learning methods.

BMC medical informatics and decision making Sep 28, 2023
BACKGROUND: Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in claims is procedure code overutilization, where one or more prescribed procedures may not be relevan...
Fraud Databases, Factual Unsupervised Machine Learning Humans Deep Learning Delivery of Health Care
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Applications of Bayesian Neural Networks in Outlier Detection.

Big data Jan 27, 2023
Anomaly detection is crucial in a variety of domains, such as fraud detection, disease diagnosis, and equipment defect detection. With the development of deep learning, anomaly detection with Bayesian neural networks (BNNs) becomes a novel research t...
Bayes Theorem Spatial Analysis Deep Learning Neural Networks, Computer Fraud
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New Software Interface for Registering Rapid Antigen Test Results to Prevent Fraud.

Disaster medicine and public health preparedness Oct 13, 2022
Donald O. Besong has already documented that the online registration of unsupervised lateral flow test results poses concerns in the case of a serious pandemic where there are not enough medics to read scans or watch videos of candidates' results (Be...
Pandemics Fraud Software Artificial Intelligence Humans
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Monitoring and Analysis of Venture Capital and Corporate Fraud Based on Deep Learning.

Computational intelligence and neuroscience May 31, 2022
With the continuous expansion of global investment institutions, the development of the investment industry is gradually accelerating, but the risks behind the investment are also constantly increasing. Using the data of A-share companies in China's ...
Investments Fraud Industry Deep Learning
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E-Commerce Fraud Detection Model by Computer Artificial Intelligence Data Mining.

Computational intelligence and neuroscience May 9, 2022
This study aims to identify e-commerce fraud, solve the financial risks of e-commerce enterprises through big data mining (BDM), further explore more effective solutions through Information fusion technology (IFT), and create an e-commerce fraud dete...
Artificial Intelligence Data Mining Computers Fraud Commerce
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Feature engineering solution with structured query language analytic functions in detecting electricity frauds using machine learning.

Scientific reports Feb 28, 2022
Detecting fraud related to electricity consumption is usually a difficult challenge as the input datasets are sometimes unreliable due to missing and inconsistent records, faults, misinterpretation of meter reading remarks, status, etc. In this paper...
Fraud Unsupervised Machine Learning Electricity Algorithms Machine Learning
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Credit card fraud detection using a hierarchical behavior-knowledge space model.

PloS one Jan 20, 2022
With the advancement in machine learning, researchers continue to devise and implement effective intelligent methods for fraud detection in the financial sector. Indeed, credit card fraud leads to billions of dollars in losses for merchants every yea...
Algorithms Machine Learning Fraud Humans
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A Novel Feature-Engineered-NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data.

Sensors (Basel, Switzerland) Dec 17, 2021
This study presents a novel feature-engineered-natural gradient descent ensemble-boosting (NGBoost) machine-learning framework for detecting fraud in power consumption data. The proposed framework was sequentially executed in three stages: data pre-p...
Algorithms Time Factors Machine Learning Fraud Electricity
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Detecting fabrication in large-scale molecular omics data.

PloS one Nov 30, 2021
Fraud is a pervasive problem and can occur as fabrication, falsification, plagiarism, or theft. The scientific community is not exempt from this universal problem and several studies have recently been caught manipulating or fabricating data. Current...
Big Data Machine Learning Scientific Misconduct Biomedical Research Fraud Humans
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