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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: | Classification and detection of eye disease from fundus images using machine learning |
| Authors Name: | Dhruvi Patel , Dr. Vikas Tulshyan , Prof. Naimish Patel |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_219287
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| Published Paper Id: | IJNRD2404674 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | The predominance of eye infections such as diabetic retinopathy, glaucoma, and age-related macular degeneration (AMD) underscores the significance of early discovery and intercession to anticipate irreversible vision misfortune. In this paper, we propose a novel approach for robotized eye malady location leveraging machine learning calculations connected to fundus pictures. Fundus pictures give a comprehensive see of the retina and its vasculature, advertising profitable data for diagnosing different visual pathologies. Our technique includes preprocessing strategies to improve picture quality, taken after by include extraction to capture discriminative designs characteristic of diverse eye maladies. We utilize state-of-the-art machine learning models, counting Manufactured neural systems (ANNs) and outfit strategies, to memorize complex representations from the extricated highlights and classify fundus pictures into particular malady categories. The execution of our proposed framework is assessed on benchmark datasets, illustrating promising comes about in terms of exactness, affectability, specificity, and region beneath the recipient working characteristic bend (AUC-ROC). Moreover, we conduct broad tests to survey the strength and generalization capability of the proposed show over differing populaces and imaging conditions. The proposed mechanized eye malady location system appears potential for integration into clinical hone, advertising a cost-effective and productive arrangement for early conclusion and administration of sight-threatening conditions, hence contributing to made strides quiet results and diminished healthcare burdens. |
| Keywords: | Machine Learning ,Fundus pictures , ANNs ,Early discovery |
| Cite Article: | "Classification and detection of eye disease from fundus images using machine learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.g616-g623, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404674.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:IJNRD2404674 Registration ID: 219287 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: g616-g623 Country: Adalaj, Gujarat, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404674 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404674 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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