AI-Powered Anomaly Detection in Human Gastrointestinal System Unveiling Hidden Disorders with the DEEP LEARNING
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
UMT, Lahore
Abstract
Three out of eight world common cancers are esophageal, stomach and colorectal cancer (CRC). These cancers are spread due to anomalies or un-detected diseases that occurred in the human gastrointestinal system. Colorectal cancer specifically is the second most death causing cancer in the world. Like esophageal and stomach cancers, colorectal cancer (CRC) has survival rate of 8% at stage IV and from the data of previous years these cancers are responsible of causing almost 9 lacs to 1 million deaths per year. And almost accounts for 1.9 million cases. According to 2023, almost 52,550 deaths occurred due to this cancer which is spread and caused due to anomalies in human gastrointestinal system. There are tons of other numerous hazardous outcomes which occur due to human gastrointestinal disease. Thus, the medical field has so far have took numerous steps to detect human gastrointestinal disease so far. Conventionally, Colonoscopy method is used to observe human lower gastrointestinal tract (GI) and with Endoscopy Gastroenterologist observe human upper gastrointestinal diseases. Gastroenterologists used to check GI diseases using these methods. Soon with the advent of Revolution and collaboration of computers in medical fields allowed Gastroenterologist to use CADx (computer aided diagnosis) systems to detect whether human gastrointestinal system is immunes to diseases and abnormalities or not. Thus, the emergence of computers in the medical field played an important role in helping doctors observe the human Gastrointestinal system. However, computer machines are more capable in screening the large medical data from real-time or pre-recorded videos to detect diseases inside Gastrointestinal System than a human eye can. Thus, it has become an uttermost need to make such deep learning models which can detect different diseases occurred in human Gastrointestinal system from both upper GI to lower colon. This will not only save the time of doctors but also allow doctors to fully focus on treating the disease rather than taking hours to detect it. In the past, multiple works were performed in training different machine learning models with different image processing techniques to enable them to classify and detect the Gastrointestinal disease. For that a couple of research are being done where there are some models which detect disease in human upper Gastrointestinal Tract and there are some specific models which detect anomalies in only intestine part.