Titlebook: Innovative Systems for Intelligent Health Informatics; Data Science, Health Faisal Saeed,Fathey Mohammed,Abdulaziz Al-Nahari Conference pro

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A CNN-Based Model for Early Melanoma Detections. AlexNet and GoogLeNet are used to classify each cancer type according to their profile features. It was found that the average classification accuracy for the above-mentioned algorithms is 90.2% and 89% respectively, providing plausible results when comparing to other existing models.

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Pulmonary Nodule Classification Based on Three Convolutional Neural Networks Modelstion. These CNNs are trained and evaluated on the LIDC-IDRI public dataset. The best result is obtained by the ensemble model, providing a larger AUC (84.66%); “area under the receiver operating characteristic curve” and 94.44% for TPR (sensitivity), with a data augmentation technique.

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on Predication Methodsessential to support these systems. They mainly rely on datasets with assumptions that match the reality. However, one of the greatest challenges to prediction methods is to have datasets which are normally distributed. This paper presents an experimental work to implement SMOTE (Synthetic Minority

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UPLX: Blockchain Platform for Integrated Health Data Managementdecide on the best medications and for the public to have their own dependable health information history as they continue with their daily lives. We propose UPLX (Unified Patient Ledger) as a blockchain-based data platform to securely record, “anonymize” and store patient health data for medical, a

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Convolutional Neural Networks for Automatic Detection of Colon Adenocarcinoma Based on Histopathologoms in the early stages of the injury, several types of tests must be performed to discover the cancer, but these methods take a lot of time, cost and require a specialized expert. So in this paper, we proposed a Convolutional Neural Network (CNN) model that characterized by speed of diagnosis and h

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Intelligent Health Informatics with Personalisation in Weather-Based Healthcare Using Machine Learni with cognitive computing would provide added value to healthcare. While the well-being and human health can be profoundly affected by weather, the effect of machine learning on personalised weather-based healthcare for self-management is unclear. This paper seeks to understand how machine learning

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A CNN-Based Model for Early Melanoma Detectionur skin its color. Early detection of these symptoms will certainly help affected people to overcome their suffering and find appropriate solutions for their treatment methods. That is why researchers have tried in many studies to provide technical solutions to help early detection of skin cancer. I

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