Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
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This Author published in this journals
All Journal International Journal of Multidisciplinary Sciences and Arts
Muhammad Ibrar
New Mexico highlands university Las Vegas, NM
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Artificial Intelligence in Healthcare: Revealing Novel Approaches to Cancer Treatment, Fraud Investigation, and Petroleum Industry Perspectives Muhammad Fahad; Muhammad Ibrar; Muhammad Umer Qayyum; Ali Husnain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4637

Abstract

Artificial Intelligence (AI) is increasingly transforming healthcare by enhancing diagnostic accuracy, personalizing treatment, and improving operational efficiencies. This review explores AI's impact across several key areas: cancer medicine, fraud detection, and lessons from the petroleum industry. In cancer medicine, AI-driven advancements are leading to more accurate diagnostics, personalized treatment plans, and predictive models for patient outcomes. In fraud detection, AI techniques such as anomaly detection and natural language processing are effectively identifying and mitigating fraudulent activities, safeguarding financial and operational integrity. Insights from the petroleum industry reveal how AI applications, such as predictive maintenance and operational optimization, can be adapted to healthcare settings to enhance equipment reliability and resource management. Emerging trends include the integration of AI with genomics, telemedicine, and cross-disciplinary innovations, which promise further advancements in personalized care and operational efficiency. However, ethical considerations such as data privacy, bias, and transparency must be addressed to ensure responsible AI deployment. The review concludes by highlighting the need for continued innovation, collaboration, and patient-centric approaches to fully realize AI's potential in transforming healthcare and improving patient outcomes.
Integrating AI in Healthcare: Innovations in Petroleum-Based Fraud Detection and Its Implications for Medical Diagnostics Muhammad Fahad; Muhammad Ibrar; Muhammad Umer Qayyum; Ali Husnain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4655

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.
Co-Authors Ali Husnain Muhammad Fahad Muhammad Umer Qayyum