Integrating AI in Healthcare: Innovations in Petroleum-Based Fraud Detection and Its Implications for Medical Diagnostics
DOI:
10.47709/ijmdsa.v3i4.4655Keywords:
Artificial Intelligence, Machine Learning, Fraud Detection, Anomaly Detection, Fraud Prevention, Data Integrity, Regulatory Compliance, Pattern Recognition, Predictive AnalyticsDimension Badge Record
Abstract
Artificial intelligence (AI) is transforming a number of industries through increasing operational effectiveness, detecting fraudulent activity, and boosting diagnostic accuracy. In order to demonstrate the transformational potential of AI techniques across different areas, this review paper examines the convergence of petroleum-based fraud detection and AI applications in healthcare. The study looks at how artificial intelligence is currently being used in healthcare, particularly in tailored and medical diagnostics. After that, it explores how artificial intelligence (AI) is utilized in petroleum-based fraud detection, going over methods like data mining, anomaly detection, and machine learning algorithms that are used to find and stop fraud. The review emphasizes the possible advantages and synergies as it looks further into how fraud detection findings from the petroleum business might be applied to healthcare. Notwithstanding these advantages, the paper discusses the main obstacles and restrictions related to integrating AI, such as system integration, data security and privacy, accuracy and dependability, and ethical and legal issues. The study intends to provide significant insights into the efficient deployment of AI technologies and the potential for cross-industry applications to stimulate innovation and enhance results by giving a thorough review of these subjects.
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Accepted Date: 2024-09-12
Published Date: 2024-09-14
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Copyright (c) 2024 Muhammad Fahad, Muhammad Ibrar, Muhammad Umer Qayyum, Ali Husnain
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