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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Threshold Methodology to Predict Brain Tumor with Gene Expression Pattern by using Machine Learning Algorithm |
| Authors Name: | Y.Tezaaw , Dr.K.Vijaya Lakshmi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_192270
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| Published Paper Id: | IJNRD2206122 |
| Published In: | Volume 7 Issue 6, June-2022 |
| DOI: | |
| Abstract: | The Tumor that has been developed in an organ of brain or spinal cord is said to be brain cancer which is further classified into several types based on its location as well as origin namely glioma, pituitary adenomas, meningioma, schwannoma and medulloblastoma. One of the most frequent from the above brain cancer is Glioma which is represented as glial cells that plays the major type in brain whereas it is further classified as pilocytic astrocytoma, medulloblastoma, glioblastoma and ependymoma based on morphological appearance. The best way of detecting cancer during earlier stage is Gene Expression (GE) which reflects biochemical processes in cells, tissues and an organism's genetic aspects. The information about gene expression helps to measure the levels of gene expression as well as generate valuable data in computational analysis through sequencing methods of Deoxyribonucleic Acid (DNA) and Ribonucleic Acid (RNA) microarrays. At present, several researchers focuses Machine Learning (ML) technique in predicting diseases using GE data. The discovery of genomes study assist in interaction among genes as well as the disease and its interaction leads for specific phenotype that developed exponentially. |
| Keywords: | Gene Expression (GE), Principal Component Analysis (PCA), hyperparameter tuning, brain cancer, Machine Learning (ML) |
| Cite Article: | "Threshold Methodology to Predict Brain Tumor with Gene Expression Pattern by using Machine Learning Algorithm", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 6, page no.1-6, June-2022, Available :http://www.ijnrd.org/papers/IJNRD2206122.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2206122 Registration ID: 192270 Published In: Volume 7 Issue 6, June-2022 DOI (Digital Object Identifier): Page No: 1-6 Country: Tirupati RURAL, Andhra Pradesh, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2206122 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2206122 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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