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  Published Paper Details:

  Paper Title

AI-Based Early Detection of Chronic Diseases Using Medical Imaging: Use deep learning to detect early signs of diseases like cancer or diabetes from X-rays or MRI scans.

  Authors

  Pooja Pawar,  Ashwini Phalkhe,  Kiran Unhale,  Aditi Jagdale,  Aaman Havaldar, VinayKhule

  Keywords

AI-Based Early Detection of Chronic Diseases Using Medical Imaging: Use deep learning to detect early signs of diseases like cancer or diabetes from X-rays or MRI scans.

  Abstract


Chronic disease significantly affects health on a global scale. Deep machine learning algorithms have found widespread application in the diagnosis of chronic diseases. Early diagnosis and treatment reduce the chance of a disease getting worse and, as a result, raise related mortality. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. This paper proposes a final year project that develops and evaluates deep-learning pipelines to detect early signs of chronic diseases from medical imagining modalities. The study includes dataset collection and curation, image preprocessing, model design, performance evaluation and explainability.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTBH02014

  Paper ID - 295200

  Page Number(s) - 65-68

  Pubished in - Volume 13 | Issue 10 | October 2025

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Pooja Pawar,  Ashwini Phalkhe,  Kiran Unhale,  Aditi Jagdale,  Aaman Havaldar, VinayKhule,   "AI-Based Early Detection of Chronic Diseases Using Medical Imaging: Use deep learning to detect early signs of diseases like cancer or diabetes from X-rays or MRI scans.", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 10, pp.65-68, October 2025, Available at :http://www.ijcrt.org/papers/IJCRTBH02014.pdf

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ISSN: 2320-2882
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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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