Automatic disease diagnosis using medical imaging has been a hot research topic in the past few years. Over the past decade, significant research efforts have been made in X-ray and CT image analysis and diagnosis of different diseases, including but not limited to laparoscopic surgical actions, kidney stone types, Alzheimer’s disease, and other general diseases like heart problems. Medical imaging is a very helpful and effective tool for the diagnosis of atypical and common symptoms. In recent years, novel and enhanced imaging methods have been developed for the effective extraction of medical images with advanced resolution and other enhanced features. However, although modern imaging modes are advanced and very effective for extraction, the interpretation of these images is still labor-intensive and requires high expertise in the relevant field. There is a growing void between the discovery of images and their interpretation due to the scarcity of expert doctors in this field. The solution is automation, and the best approach to deploy such automation at a grand scale in real life is to utilize AI. Artificial intelligence comprises various fields that assist in tackling tough problems in automation, such as computer vision, natural language processing, and robotics.
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Ranjith et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69d893eb6c1944d70ce04d5e — DOI: https://doi.org/10.56975/ijvra.v4i3.702283
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:
Gundam Ranjith
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Martin College
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