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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)

International Peer Reviewed & Refereed Journals, Open Access Journal

IJCRT Peer-Reviewed (Refereed) Journal as Per New UGC Rules.

ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013

Call For Paper - Volume 14 | Issue 8 | Month- August 2026

Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 7.97 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(CrossRef DOI)

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  Published Paper Details:

  Paper Title

RetinoScopeAI: Retinal OCT Prediction Paltform

  Authors

  Prof. Bhagyashri Thakare,  Dr. Bhushan Chaudhari,  Durgesh Wagh,  Kalpesh Chaudhari,  Amol Jaiswal, Rutik gayakwad

  Keywords

AI-driven diagnosis, retinal OCT imaging, deep learning models, automated retinal analysis, early eye disease detec- tion, clinical decision support, telemedicine ophthalmology

  Abstract


RetinoScopeAI is an OCT retinal prediction platform that was created using AI to deliver precise and early identification of reti-nal conditions like Choroidal Ne- ovascularization (CNV), Dia-betic Macular Edema (DME), and Drusen. It is a system that involves deep learning algo- rithms to decode high-resolution Optical Coherence Tomog- raphy (OCT) images. Such images are initially optimized by performing preprocessing on the image to remove noise and enhance the clarity of the image. Once preprocessed, the im- ages go through a trained neural network and disease-spe- cific patterns in the layers on the eye are detected. The site offers secure and easy web interface to physicians and healthcare providers. Users are able to send OCT images and get real-time results of diagnosis. The system shows the pre- dicted disease as well as the visual finding of the OCT scan. It can also give confidence scores and clinical insights to make medical decisions. RetinoScopeAI will help eliminate the reliance on manual interpretation by professionals. This reduces the human error and enhances consistency in diag- nosis. The platform aids in early detection and this aids in preventing loss of vision. It also can be used in remote and tele-ophthalmology. The automatic analysis saves time on the part of the doctors and more efficient on the screen-ing. Ret- inoScopeAI is an AI-based medical imaging company that creates better patient care. In general, the platform provides an efficient, rapid, and smart way of diagnosing and man- management of retinal diseases.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTBW02039

  Paper ID - 309377

  Page Number(s) - 230-237

  Pubished in - Volume 14 | Issue 6 | June 2026

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Prof. Bhagyashri Thakare,  Dr. Bhushan Chaudhari,  Durgesh Wagh,  Kalpesh Chaudhari,  Amol Jaiswal, Rutik gayakwad,   "RetinoScopeAI: Retinal OCT Prediction Paltform", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 6, pp.230-237, June 2026, Available at :http://www.ijcrt.org/papers/IJCRTBW02039.pdf

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Call For Paper August 2026
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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