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E-grāmata: Innovative Systems for Intelligent Health Informatics: Data Science, Health Informatics, Intelligent Systems, Smart Computing

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This book presents the papers included in the proceedings of the 5th International Conference of Reliable Information and Communication Technology 2020 (IRICT 2020) that was held virtually on December 21–22, 2020. The main theme of the book is “Innovative Systems for Intelligent Health Informatics”. A total of 140 papers were submitted to the conference, but only 111 papers were published in this book. The book presents several hot research topics which include health informatics, bioinformatics, information retrieval, artificial intelligence, soft computing, data science, big data analytics, Internet of things (IoT), intelligent communication systems, information security, information systems, and software engineering. 
Comparative Study of SMOTE and Bootstrapping Performance based on Predication Methods.- UPLX: Blockchain Platform for Integrated Health Data Management.- Convolutional Neural Networks for Automatic Detection of Colon Ad-enocarcinoma Based on Histopathological Images.- Intelligent Health Informatics with Personalisation in Weather-based Healthcare using Machine Learning.- A CNN-based Model for Early Melanoma Detection.- SMARTS D4D Application Module for Dietary Adherence Self-Monitoring among Hemodialysis Patients.- Improved Multi-Label Medical Text Classification using Features Cooperation.- Image Modeling through Augmented Reality for Skin Allergies Recognition.- Hybridisation of Optimised Support Vector Machine and Artificial Neural Network for Diabetic Retinopathy Classification.- A Habit-Change Support Web-Based System with Big Data Analytical Features for Hospitals (Doctive).- An Architecture for Intelligent Diagnosing Diabetic Types and Com-plications Based on Symptoms.- An Advanced Encryption Cryptographically-based Securing Applica-tive Protocols MQTT and CoAP to Optimize Medical-IOT Supervis-ing Platforms.- Pulmonary Nodule Classification Based on Three Convolutional Neural Networks Models.