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  Published Paper Details:

  Paper Title

Explaining Autonomous Pneumonia Disease Detection Using Grad-CAM For Improved Decision Support

  Authors

  Om Chavan,  Yash Bijoor,  Chahat Kothari,  Arjun Jaiswal

  Keywords

artificial intelligence, machine learning, black box, explainability, transparency, interpretablility

  Abstract


In recent years, artificial intelligence and machine learning has made major strides in the field of medicine. The medical sector requires a high level of accountability and transparency. Reliable machine decisions and predictions require explanations to justify their outcomes. This necessitates increased interpretability and a deeper understanding of the underlying mechanisms of algorithms. However, the black box nature of deep learning remains a challenge, leading to limited comprehension of many machine decisions. The reason radiologists are weary of using AI is because they do not trust model predictions without any form of explainability. Thus, we aim to create a system that not only focuses on interpretability and explainability but also has a high enough accuracy to make it reliable enough to be trusted and used by radiologists.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2312674

  Paper ID - 248439

  Page Number(s) - g35-g43

  Pubished in - Volume 11 | Issue 12 | December 2023

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Om Chavan,  Yash Bijoor,  Chahat Kothari,  Arjun Jaiswal,   "Explaining Autonomous Pneumonia Disease Detection Using Grad-CAM For Improved Decision Support", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 12, pp.g35-g43, December 2023, Available at :http://www.ijcrt.org/papers/IJCRT2312674.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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