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  • Role_of_Artificial_Intelligence_and_Vibrational_Spectroscopy_in_Cancer_Diagnostics__IUR-F__

    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Expert Review of Molecular Diagnostics on 27/06/2020 available online: https://www.tandfonline.com/doi/abs/10.1080/14737159.2020.1784008

    Accepted author manuscript, 733 KB, PDF document

    Embargo ends: 27/06/21

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics

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<mark>Journal publication date</mark>1/08/2020
<mark>Journal</mark>Expert Review of Molecular Diagnostics
Issue number8
Volume20
Number of pages7
Pages (from-to)749-755
Publication StatusPublished
Early online date27/06/20
<mark>Original language</mark>English

Abstract

Introduction: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These techniques can be used not only for the early diagnosis of cancer but also for monitoring the progression of the disease. Furthermore, chemical pathways to the progression of the disease process can be understood and followed. Areas covered: More recently, Artificial Intelligence (AI), Neural Network (NN), and Machine Learning are being combined with spectroscopy, which is making it easier to understand the chemical structural details of cancers and biological molecules more precisely and accurately. In this report, these aspects are being outlined by using breast cancer as a specific example. Expert opinion: A pathway showing to combine vibrational spectroscopy with AI and ML has immense potential in predicting various stages of different disease processes, in particular, in cancer diagnosis, staging, and designing treatment. This will result in improved patient care pathways.

Bibliographic note

This is an Accepted Manuscript of an article published by Taylor & Francis in Expert Review of Molecular Diagnostics on 27/06/2020 available online: https://www.tandfonline.com/doi/abs/10.1080/14737159.2020.1784008