Special Issue "AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems"

Submission Deadline: 30 December 2020
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Guest Editors
Dr. Mazin Abed Mohammed, University of Anbar, Iraq.
Dr. Mohd Khanapi Abd Ghani, Universiti Teknikal Malaysia Melaka, Malaysia.
Dr. Mashael S. Maashi, King Saud University, Saudi Arabia.
Dr. Jon Arambarri, ESTIA, France.

Summary

Artificial intelligence (AI) and its applications are now the hottest research areas. In recent years, there have been more and more AI applications in the medical field. AI technology is promoting the development of the medical and health industries. In the medical domain, AI techniques can be used to develop clinical decision support systems to help with medical diagnostics. AI technologies can be also deployed in various medical devices, trackers, and information systems. A huge amount of patient data is recorded in the electronic medical record (EMR) database, including diagnosis, medical history, medications, and lab results. Through the process of extraction, transformation, and loading (ETL), researchers can generate a patient dataset worthy of analysis by AI techniques. In addition to the data analysis using structure data, AI techniques are now used for medical image recognition, medical text, and semantic recognition, and molecular biological testing. The analysis results can be used as a reference for the evaluation of patients by the medical team. Recently, AI, internet-of-things (IoT), big data analytics, machine learning, deep learning, Fog Computing, cloud computing and block chain technologies have been intelligently applied with various applications in networking, Medical diagnosis and Healthcare Systems, shipping to build efficient, sustainable systems and Intelligent Solutions to Medical and Healthcare Systems.

This Special Issue focus on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems. Biomedical data play a fundamental role in many fields of research and clinical practice. Very often the complexity of these data and their large volume makes it necessary to develop advanced analysis techniques and systems. Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging, requires new signal processing and machine learning methods. The recent progress in machine learning techniques, and in particular deep learning, has revolutionized various fields of artificial vision, significantly pushing the state of the art of artificial vision systems into a wide range of high-level tasks. Such progress can help address problems in the analysis of biomedical data.


Keywords
This Special Issue seeks original, high-quality contributions that investigate AI applications in healthcare. The main topics of interest include but are not limited to the following:
• AI and big data analytics applied in medical domain;
• AI methodologies for medical data analysis;
• Administrative data analysis using AI techniques;
• Intelligent medical efficient solutions for future applications;
• AI and block chain assisted medical efficient product designs;
• Optimization of medical assets using machine learning and deep learning techniques;
• Smart IoT sensor design and optimal utilization in Healthcare Systems;
• Applications of artificial intelligence, block chain IoT for sustainable medical and service;
• AI based intelligent solutions for Healthcare Systems;
• Machine learning applied to Healthcare Systems;
• AI solutions to intelligent transportation systems;
• Medical data acquisition, cleaning and integration using AI methodologies;
• Medical image recognition using AI technologies;
• Natural language processing in medical documents;
• Computer-aided diagnosis;
• Artificial neural networks;
• Machine learning;
• Deep learning;
• COVID-19 Epidemiology • Machine and deep learning approaches based observation in case of COVID-19;
• Computational correlation in pneumonia and COVID-19;
• Computational methods for COVID-19 prediction and detection;
• Data mining and knowledge discovery in healthcare;
• Decision support systems for healthcare and wellbeing;
• Optimization for symptoms detection;
• Medical expert systems;
• Applications of artificial intelligence techniques in in case of COVID-19;
• Intelligent computing and platforms;
• Big data frameworks and architectures for applied computation;
• Visualization and interactive interfaces in case of COVID-19;
• Role of machine learning and computational methods in mental stress observations due to lockdown;
• COVID-19 analysis using Big Data;
• COVID-19 analysis using pattern recognition;
• Medical imaging using computer vision for COVID-19;
• Information Technology participation in Patient monitoring and tracking for COVID-19;
• Medical Management system for COVID-19;
• Treatment simulation model and analysis for COVID-19;
• Telemedicine system for COVID-19;
• Big Data Analytics for prediction and application for COVID-19;
• Big data analytics for prediction in medicine and health related applications;
• Medical Pattern recognition;
• Medical Image reconstruction;
• Multi-modality fusion;
• Statistical Medical pattern recognition;
• Medical Segmentation;
• Medical Image fusion;
• Medical Image retrieval. biological imaging Molecular/pathologic image analysis gene data analysis multiple modalities X-ray CT MRI PET ultrasound;