The Integral Role of Digital Technologies and Medical Laboratories in Epidemic Prediction and Healthcare Enhancement

Authors

  • Jawaher Jadid A. Al-Anazi: Fatimah Khalaf Alanazi: Abdulmajeed Osama Saber: Majed Mubarak Ali Al-Yami: Yousef Miqed Alharbi: Waleed Abdulaziz Almahbub: Hassan Nasser Almarqan: Nada Moshref Mashani Althobiani:

DOI:

https://doi.org/10.63278/jicrcr.vi.716

Keywords:

Medical Laboratories, Epidemiology, Digital Technologies, Big Data, Healthcare Systems.

Abstract

The evolution of healthcare systems has significantly benefited from technological advancements, particularly in medical laboratories and epidemiology. With the rise of digital applications and artificial intelligence, the precision of disease diagnostics, epidemic prediction, and treatment decisions has improved dramatically. Medical laboratories now play a central role not only in diagnosing diseases but also in monitoring their progression, detecting emerging threats, and guiding treatment choices. Furthermore, the integration of big data through mobile health applications, electronic health records, and social media has enhanced the capabilities of medical laboratories in managing epidemics such as COVID-19. This paper explores the multifaceted role of medical laboratories in healthcare, highlighting the contributions of automated systems, next-generation sequencing, mass spectrometry, digital pathology, and point-of-care testing. It also discusses the collaboration between medical laboratory technicians and epidemiologists, which is crucial for effective diagnosis, treatment, and public health responses.

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Published

2024-03-12

How to Cite

Jawaher Jadid A. Al-Anazi: Fatimah Khalaf Alanazi: Abdulmajeed Osama Saber: Majed Mubarak Ali Al-Yami: Yousef Miqed Alharbi: Waleed Abdulaziz Almahbub: Hassan Nasser Almarqan: Nada Moshref Mashani Althobiani:. (2024). The Integral Role of Digital Technologies and Medical Laboratories in Epidemic Prediction and Healthcare Enhancement. Journal of International Crisis and Risk Communication Research , 102–108. https://doi.org/10.63278/jicrcr.vi.716

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Section

Articles