A REVIEW ON ARTIFICIAL INTELLIGENCE APPLIED ON RAMAN SPECTROSCOPY FOR MULTITUDINOUS CANCERS

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Mrs Pallavi Badarala; Dr V Bhaskara raju; Ms Tejaswi Geddada; Ms V S A A SRI VYSHNAVI SUDARSANAM; Ms Rapolu Lakshmi sowjanya; Ms Gudala Krishna Goutami

A REVIEW ON ARTIFICIAL INTELLIGENCE APPLIED ON RAMAN SPECTROSCOPY FOR MULTITUDINOUS CANCERS

Authors: Mrs Pallavi Badarala, Dr V Bhaskara raju, Ms Tejaswi Geddada, Ms V S A A SRI VYSHNAVI SUDARSANAM, Ms Rapolu Lakshmi sowjanya, Ms Gudala Krishna Goutami

Unique Paper ID: 171045
Volume: 11
Issue: 7
PageNo: 2801-2807

Keywords: Artificial Intelligence Diagnosis Machine Learning Raman spectroscopy Tumor

Abstract:
Raman spectroscopy is a label-free optical method that has been used extensively for tumor diagnosis. Using conventional diagnostic techniques, tumors can be categorized as benign, malignant, or subtypes based on the various Raman technologies. First, the cells were evaluated structurally and spectrally. Following that, the cells' Raman data was efficiently examined utilizing a variety of machine learning methods, such as neural networks and multivariate models, which were all assessed simultaneously. The reports unequivocally demonstrate the effectiveness of AI assisted Raman spectroscopy for neoplasm cell classification and prediction, with an accuracy of correct predictions on a single spectrum. A molecular probe previously reported the ability of Raman spectroscopy to discriminate between tumor and healthy tissue. Present a quick, quantitative, probabilistic tumor assessment that incorporates real-time error analysis.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 7
PageNo: 2801-2807

A REVIEW ON ARTIFICIAL INTELLIGENCE APPLIED ON RAMAN SPECTROSCOPY FOR MULTITUDINOUS CANCERS

Available:https://ijirt.org/article?manuscript=171045

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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