Hybrid Classifier for Prediction of Gastro-Intestinal Diseases from Endoscopic Images

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The healthcare industry is not similar like other industries. Healthcare is a sector that is of high priority, where the people expect very high level of care and service (Laurenza E et al. 2018). However, until now this did not satisfy the expectations socially, even though it is allocated with larger percentage of budget. Until date, only professional medical expert does interpretation of medical dataset (like endoscopy images). However, this interpretation is limited due to the subject, image complexness, multi-variations that is over various interpreters and weariness. Therefore, computational medical image processing methods has a greater scope over the future applications in the health industry. It is not so easy to use the medical image dataset for obtaining the expected results in medical image processing since the distractions over the captured dataset is not easily predictable (Birkfellner Wolfgang 2019). Over earlier days, the data of healthcare was fewer. However, due to growing developments the data evolved is getting large which makes the analysis very interesting with lot of challenges.

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