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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 23479
Article Published : 9055
Total Authors : 24029
Total Reviewer : 831
Total Countries : 162
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| Paper Title: | Hybrid Algorithm For Blood Cancer Analysis |
| Authors Name: | UMASHANKAR , HARISH , JAYANTHAN , PRANESH , SUGITHA |
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IJRTI_201213
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| Published Paper Id: | IJRTI2603069 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | |
| Abstract: | Blood cancer is still prevalent and one of the biggest health issues affecting people globally. The various subtypes of blood cancers like leukemia, lymphoma, and others require innovative technologies if one is to consider improving the precision and efficiency of diagnosis. Hence, this research attempts to design an effective and sophisticated system of blood cancer detection using hybrid deep learning approaches specifically CNN and networks. Given the blood smear image datasets as well as the training data after appropriate processing, the hybrid CNNLSTM method identifies both spatial and sequential features with the aim of enhancing the classification accuracy. The effectiveness of the system in detecting and classifying the blood cancer types is evaluated quantitatively through accuracy, confusion matrices and classification reports. Making it reliable this research advanced the area of medical diagnosis by automating and easing ways through which early blood cancers could be diagnosed thus improving the prognosis of sufferers as well as aiding in clinical decision making. |
| Keywords: | Blood Cancer Detection, Convolutional Neural Network, Long Short-Term Memory, Deep Learning, Medical Image Analysis |
| Cite Article: | "Hybrid Algorithm For Blood Cancer Analysis", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.a539-a544, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603069.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI2603069
Registration ID:201213
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier):
Page No: a539-a544 Country: Coimbatore, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603069 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603069 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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