Abnormalities of the gastrointestinal tract are widespread worldwide ***,an effective way to diagnose these life-threatening diseases is based on endoscopy,which comprises a vast number of ***,the main challenge in th...
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Abnormalities of the gastrointestinal tract are widespread worldwide ***,an effective way to diagnose these life-threatening diseases is based on endoscopy,which comprises a vast number of ***,the main challenge in this area is that the process is time-consuming and fatiguing for a gastroenterologist to examine every image in the ***,this led to the rise of studies on designingAI-based systems to assist physicians in the *** several medical imaging tasks,deep learning methods,especially convolutional neural networks(CNNs),have contributed to the stateof-the-art outcomes,where the complicated nonlinear relation between target classes and data can be learned and not limit to hand-crafted *** the other hand,hyperparameters are commonly set manually,which may take a long time and leave the risk of non-optimal hyperparameters for *** effective tool for tuning optimal hyperparameters of deep CNNis bayesian ***,due to the complexity of the CNN,the network can be regarded as a black-box model where the information stored within it is hard to ***,Explainable Artificial Intelligence(XAI)techniques are applied to overcome this issue by interpreting the decisions of the CNNs in such wise the physicians can *** play an essential role in real-time medical diagnosis,CNN-based models need to be accurate and interpretable,while the uncertainty must be ***,a novel method comprising of three phases is proposed to classify these life-threatening *** first,hyperparameter tuning is performed using bayesianoptimization for two state-of-the-art deep CNNs,and then Darknet53 and InceptionV3 features are extracted from these fine-tunned ***,XAI techniques are used to interpret which part of the images CNN takes for feature *** last,the features are fused,and uncertainties are handled by selecting entropybased *** experimental results show that the
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