Muhammad Umar¹*, Zeib Jahangir², Qurat-ul-Ain³, Fiza Saeed⁴, Sheena Shiwlani⁵ and Ashish Shiwlani⁶

¹Department of Computer Science, Illinois Institute of Technology, USA
²Department of Computer Science,William Jessup University San Jose, California, USA
³Gastroenterology, Buch International Hospital Buch Villas, Multan
⁴Department of Biomedical, Engineering University of Texas Arlington, Texas, USA
⁵Biorepository & Pathology CoRE, Mount Sinai Hospital, New York City, New York, USA
⁶College of Computing, Illinois Institute of Technology Chicago, Chicago, USA

*Corresponding Author: Muhammad Umar, Department of Computer Science, Illinois Institute of Technology, USA.

Received: June 06, 2024; Published: July 31, 2024

Abstract

Hepatitis infection is still a major global health concern, requiring effective measures to screen and manage it so that its impacts are reduced specifically hepatitis C. The past few years have seen the coming up of using AI and ML technologies together thus promising better ways of screening for hepatitis C and caring for the patients thus making everything better. In this article, some of the most real-life benefits of using Artificial Intelligence (AI) and Machine Learning (ML) for diagnosing hepatitis C are highlighted. This paper will first analyze the diagnostic methods for hepatitis C. It is important to note that the significance of artificial intelligence in examining radiological findings using imaging techniques like CT scans, MRI scans, and Ultrasound results cannot be overemphasized. The articlediscusses the ethics and rules related to AI use in healthcare, such as hepatitis C testing. If patient data is mishandled, trust deteriorates, making it hard for any computer system to access or control it. Such breaches of privacy during AI-assisted screenings could turn people away from thesetechnologies and towards less precise traditional methods. Despite these challenges, folks think there's a big chance to identify and avoid hepatitis C using AI and Machine Learning (ML). These tools could boost screenings, predict outbreaks, and improve treatments. This changes how we care for hepatitis C patients. By leveraging large datasets and state-of-the-art algorithms, AI-supported screening systems can totally change the way diseases are detected as well as its effects on public health. In conclusion, the review highlights the significant impact of AI and ML technologies in enhancing hepatitis C screening, diagnosis, and management. Using AI algorithms can enable healthcare systems to improve detection rates at an early stage, come up with optimized therapeutic strategies thus easing burden of hepatitis C on both individuals and healthcare systems.

Keywords: Hepatitis C Virus ( HCV); Artificial Intelligence (AI); Machine Learning (ML); AI Algorithms; HCV Staging; Public Health Impact.

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Citation

Citation: Muhammad Umar., et al. “Machine Learning Insights: Enhancing Hepatitis C Screening Efforts for Improved Patient Outcome".Acta Scientific Gastrointestinal Disorders 7.8 (2024): 41-52.

Copyright

Copyright: © 2024 Muhammad Umar., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.