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

• Published in: Indian journal of pathology & microbiology Vol. 64; no. 5; pp. 63 - 68
• Main Authors: Pandey, Ishan, Misra, Vatsala, Pandey, Aprajita, Ramteke, Pramod, Agrawal, Ranjan
• Format: Journal Article
• Language: English
• Published: Mumbai Wolters Kluwer India Pvt. Ltd 01.06.2021; Medknow Publications and Media Pvt. Ltd; Medknow Publications & Media Pvt. Ltd; Wolters Kluwer Medknow Publications
• Subjects: Algorithms; Artificial intelligence; Biomarkers; Cable television broadcasting industry; Cancer; Computational linguistics; Computer architecture; Computer programs; convoluted neural network; Deep learning; Development and progression; Diagnosis; Digital imaging; Epidermal growth factor; Epidermal growth factor receptors; ErbB-2 protein; Evidence-based medicine; Fluorescence; Fluorescence in situ hybridization; Gastric cancer; Growth factor receptors; Growth factors; her2/neu; Image analysis; Image enhancement; Image processing; imagej; Immunohistochemistry; Immunotherapy; Industrial research; Kinases; Language processing; Learning algorithms; Machine learning; Medical imaging equipment; Mimicry; Natural language interfaces; Neural networks; Oncology, Experimental; Precision medicine; Problem solving; Product enhancement; Protein-tyrosine kinase; R&D; Receptors; Research & development; Skills; Social networks; Software; Stomach cancer; Tyrosine; United States; United States; Fluorescence in-situ Hybridization; ImageJ; Immunohistochemistry; Artificial Intelligence; Gastric Cancer; HER2/neu; Convoluted Neural Network
• ISSN: 0377-4929; 0974-5130; 0974-5130
• DOI: 10.4103/IJPM.IJPM_950_20

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.