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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 112
Article Submitted : 17346
Article Published : 7552
Total Authors : 20065
Total Reviewer : 733
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| Paper Title: | CNN Model-Based Alzheimer`s Disease Identification on MRI Dataset: A Potential Method |
| Authors Name: | Gauri Paithankar , Rahul Inchal , Raj Yadav , Syed Mufassir Yaseen |
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IJRTI_190030
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| Published Paper Id: | IJRTI2406044 |
| Published In: | Volume 9 Issue 6, June-2024 |
| DOI: | |
| Abstract: | Alzheimer's illness could be a neurological ailment related to cognitive decay and memory misfortune. MRI is utilized to distinguish basic brain anomalies related to Alzheimer's. Profound learning, especially CNNs, has appeared to guarantee quick and dependable handling of therapeutic symbolism such as MRI looks for markers of Alzheimer's malady. This consideration examines the viability of Convolutional Neural Systems (CNNs) in distinguishing Alzheimer's illness based on brain imaging information. They think about utilizing a multi-class classification approach, recognizing between four categories. The CNN demonstrates beats desires, accomplishing an exceptional 95% accuracy on already obscure test information. Preparing and approval misfortunes of 0.06% and 0.17%, individually, propose that the learning handle was effective and did not overfit. The F1-score (94.84%), exactness (95.01%), and review (94.84%) all contribute to the survey of the model's capacity to analyze Alzheimer's infection. These discoveries propose that CNN-based procedures have viable applications in Alzheimer's infection determination. Be that as it may, assistance consideration and approval are fundamental to demonstrate the recommended approach's unwavering quality and generalizability. |
| Keywords: | Alzheimer's disease (AD), Magnetic Resonance Imaging (MRI), Deep learning techniques, Convolutional Neural Networks (CNNs), Early detection, Classification. |
| Cite Article: | "CNN Model-Based Alzheimer`s Disease Identification on MRI Dataset: A Potential Method", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 6, page no.331 - 339, June-2024, Available :http://www.ijrti.org/papers/IJRTI2406044.pdf |
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| ISSN: |
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: IJRTI2406044
Registration ID:190030
Published In: Volume 9 Issue 6, June-2024
DOI (Digital Object Identifier):
Page No: 331 - 339 Country: Pune, Maharashtra, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2406044 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2406044 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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