Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer

In recent clinical practice the molecular diagnostics have been significantly empowered and upgraded by the use of Artificial Intelligence and its assisted technologies. The use of Machine leaning and Deep Learning Neural network architectures have brought in a new dimension in clinical oncological...

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Autores principales:	Ishan Pandey, Vatsala Misra, Aprajita T Pandey, Pramod W Ramteke, Ranjan Agrawal
Formato:	article
Lenguaje:	EN
Publicado:	Wolters Kluwer Medknow Publications 2021
Materias:	artificial intelligence convoluted neural network fluorescence in-situ hybridization gastric cancer her2/neu imagej immunohistochemistry Pathology RB1-214 Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/90ae1ff6dc674db1b6baca514e70c98f
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id	oai:doaj.org-article:90ae1ff6dc674db1b6baca514e70c98f
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spelling	oai:doaj.org-article:90ae1ff6dc674db1b6baca514e70c98f2021-12-02T17:49:10ZArtificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer0377-492910.4103/IJPM.IJPM_950_20https://doaj.org/article/90ae1ff6dc674db1b6baca514e70c98f2021-01-01T00:00:00Zhttp://www.ijpmonline.org/article.asp?issn=0377-4929;year=2021;volume=64;issue=5;spage=63;epage=68;aulast=Pandeyhttps://doaj.org/toc/0377-4929In recent clinical practice the molecular diagnostics have been significantly empowered and upgraded by the use of Artificial Intelligence and its assisted technologies. The use of Machine leaning and Deep Learning Neural network architectures have brought in a new dimension in clinical oncological research and development. These algorithm based software system with enhanced digital image analysis have emerged into a new branch of digital pathology and contributed immensely towards precision medicine and personal diagnostics. In India, gastric cancer is one of the most common cancers in males as well as in females. Various molecular biomarkers are associated with gastric cancer development and progression of which HER2 protein, a transmembrane tyrosine kinase (TK) receptor of epidermal growth factor receptors (EGFRs) family is of prime importance. The EGF receptor expression in gastric cancer is linked with its prognostics and theragnostics. These expressions are assessed by immunohistochemistry (IHC) and molecular techniques such as Fluorescence in-situ hybridization (FISH), as per recommendations for HER2 targeted immunotherapy. These have motivated the software giants like Google Inc. to produce innovative state of art technologies mimicking human traits such as learning and problem solving skill sets. This field is still under development and is slowly evolving and capturing global importance in recent times. A literature search on PubMed was performed to access updated information for this manuscript.Ishan PandeyVatsala MisraAprajita T PandeyPramod W RamtekeRanjan AgrawalWolters Kluwer Medknow Publicationsarticleartificial intelligenceconvoluted neural networkfluorescence in-situ hybridizationgastric cancerher2/neuimagejimmunohistochemistryPathologyRB1-214MicrobiologyQR1-502ENIndian Journal of Pathology and Microbiology, Vol 64, Iss 5, Pp 63-68 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence convoluted neural network fluorescence in-situ hybridization gastric cancer her2/neu imagej immunohistochemistry Pathology RB1-214 Microbiology QR1-502
spellingShingle	artificial intelligence convoluted neural network fluorescence in-situ hybridization gastric cancer her2/neu imagej immunohistochemistry Pathology RB1-214 Microbiology QR1-502 Ishan Pandey Vatsala Misra Aprajita T Pandey Pramod W Ramteke Ranjan Agrawal Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
description	In recent clinical practice the molecular diagnostics have been significantly empowered and upgraded by the use of Artificial Intelligence and its assisted technologies. The use of Machine leaning and Deep Learning Neural network architectures have brought in a new dimension in clinical oncological research and development. These algorithm based software system with enhanced digital image analysis have emerged into a new branch of digital pathology and contributed immensely towards precision medicine and personal diagnostics. In India, gastric cancer is one of the most common cancers in males as well as in females. Various molecular biomarkers are associated with gastric cancer development and progression of which HER2 protein, a transmembrane tyrosine kinase (TK) receptor of epidermal growth factor receptors (EGFRs) family is of prime importance. The EGF receptor expression in gastric cancer is linked with its prognostics and theragnostics. These expressions are assessed by immunohistochemistry (IHC) and molecular techniques such as Fluorescence in-situ hybridization (FISH), as per recommendations for HER2 targeted immunotherapy. These have motivated the software giants like Google Inc. to produce innovative state of art technologies mimicking human traits such as learning and problem solving skill sets. This field is still under development and is slowly evolving and capturing global importance in recent times. A literature search on PubMed was performed to access updated information for this manuscript.
format	article
author	Ishan Pandey Vatsala Misra Aprajita T Pandey Pramod W Ramteke Ranjan Agrawal
author_facet	Ishan Pandey Vatsala Misra Aprajita T Pandey Pramod W Ramteke Ranjan Agrawal
author_sort	Ishan Pandey
title	Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
title_short	Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
title_full	Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
title_fullStr	Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
title_full_unstemmed	Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
title_sort	artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer
publisher	Wolters Kluwer Medknow Publications
publishDate	2021
url	https://doaj.org/article/90ae1ff6dc674db1b6baca514e70c98f
work_keys_str_mv	AT ishanpandey artificialintelligencetechnologiesempoweringidentificationofnoveldiagnosticmolecularmarkersingastriccancer AT vatsalamisra artificialintelligencetechnologiesempoweringidentificationofnoveldiagnosticmolecularmarkersingastriccancer AT aprajitatpandey artificialintelligencetechnologiesempoweringidentificationofnoveldiagnosticmolecularmarkersingastriccancer AT pramodwramteke artificialintelligencetechnologiesempoweringidentificationofnoveldiagnosticmolecularmarkersingastriccancer AT ranjanagrawal artificialintelligencetechnologiesempoweringidentificationofnoveldiagnosticmolecularmarkersingastriccancer
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Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer

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