Calls for Papers (special): International Journal of Reliable and Quality E-Healthcare (IJRQEH)


Special Issue On: Application of AI and Blockchain Technology in Healthcare

Submission Due Date
2/28/2022

Guest Editors
Bipin Kumar Rai, ABES Institute of Technology, India
Gautam Kumar, CMR Engineering College, India
Jabar Yousif, Sohar University, Oman

Introduction
Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce role of middleman, one of the most important regulatory actors in our society.

Blockchain technology enables a decentralized and distributed environment with no need for a central authority. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is healthcare, due to the need for a more patient-centric approach to healthcare systems and to connect disparate systems and increase the accuracy of electronic healthcare records (EHRs).

Objective
In this special session, an analysis of state-of-the-art blockchain and AI research in the field of healthcare will be considered.

Recommended Topics
  • Digital Transformation of Healthcare
  • Use of blockchain in Healthcare Patient and Clinical Research
  • Blockchain for Medication Administration Records
  • Ensuring Privacy and security of healthcare data using blockchain
  • Using blockchain Managing electronic medical record (EMR)
  • data Protection of healthcare data using blockchain
  • Personal health record data management using blockchainMachine Learning for Precision Medicine and Preventive Healthcare
  • Machine Learning for Identifying diseases and diagnosis
  • Machine Learning for Drug discovery and manufacturing
  • Machine Learning for Smart health records
  • Machine Learning for Clinical Trial and research
  • Machine learning and deep learning for Biomedical and Health Informatics
  • Machine Learning in Rule Based Expert Systems- Used in EHR (Electronic Health record)
  • AI and ML applications in Clinical Trial Research


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Application of AI and Blockchain Technology in Healthcare on or before February 28th, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Bipin Kumar Rai
Gautam Kumar
Jabar Yousif
Guest Editors
International Journal of Reliable and Quality E-Healthcare (IJRQEH)
Email: Bipinkrai@gmail.com; gautam21ujrb@gmail.com; jyousif@su.edu.om

Special Issue On: Recent Advances in Medical Image Analysis using Machine Learning and Deep Learning for Health Care Applications

Submission Due Date
3/1/2022

Guest Editors
Manoj Diwakar, Graphic Era Deemed to be University, Dehradun, India
Prabhishek Singh, Amity University, India

Introduction
A new digital world brings about new technologies like machine learning and deep learning, and this further can provide intriguing and notable results with regards to circumstances that are yet unknown in the field of medical imaging. The machine learning and deep learning offers many answers to many problems found in medical imaging and health care applications. Medical imaging is a process in which various imaging procedures are used to collect visual information about the interior structures of the body to provide an assessment of the illness and to provide treatment to it. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. To quantify such large medical imaging data, machine learning and deep learning carried out different algorithms such as support vector machine, convolutional neural network etc to solve this problem. There are various applications of medical image analysis that include: medical image denoising, medical image super resolution, multi-modal image fusion, medical image registration, medical image segmentation, medical image super-resolution, diagnose abnormalities in medical images, medical image synthesis etc.

This special issue is meant to give an awareness of medical image analysis and many techniques and algorithms used to analyse medical data. It also focuses on current achievements and latest developments in medical imaging and health care applications and to identify latest cutting-edge techniques of machine learning and deep learning in this domain.

Objective
The major objectives of the special issue are to:
• Extract advance scientific research within the broad field of health care and medical image analysis problems; and
• Have experts, academicians, researchers, and scientists share their achievement stories and research issues for applying advanced machine learning and deep learning techniques to the real-world health care and medical image analysis problems. We invite submissions successfully applying unconventional machine learning and deep learning techniques to the real-time medical imaging and health care problems by addressing to life-saving issues.

Recommended Topics
• Medical (CT, MRI, Ultrasound..etc) Image reconstruction.
• Multi-modality Medical (CT, MRI, Ultrasound..etc) image fusion.
• Medical image retrieval.
• Machine learning and Deep learning based medical image analysis and enhancement.
• Development in healthcare application using machine learning and deep learning.
• Intelligent steganalysis for Medical image based on machine learning and deep learning.
• Medical Image forensics based on machine learning and deep learning.
• Robust, fragile, and semi-fragile watermarking for medical image processing
• Medical image denoising.
• Diseases Prediction and its classification.
• Diagnosis of fatal Disease.
• Abnormality Detection.
• 3D-medical imaging
• Brain, Chest, Breast, Cardiac, and Musculo-skeletal imaging using machine learning and deep learning.
• Machine Learning and Deep Learning techniques for medical image analysis.
• Population health and Patient progress management in Health Care Applications.
• Predicting and preventing risks in Health Care Applications

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Recent Advances in Medical Image Analysis using Machine Learning and Deep Learning for Health Care Applications on or before March 1st, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Manoj Diwakar
Prabhishek Singh
Guest Editors
International Journal of Reliable and Quality E-Healthcare (IJRQEH)
Email: manoj.diwakar@gmail.com; prabhisheksingh88@gmail.com

Special Issue On: Multimedia Data Management using Emerging Technologies in Healthcare Applications

Submission Due Date
6/30/2022

Guest Editors
Gaurav Dhiman
Government Bikram College, India

Atulya K. Nagar
Liverpool Hope University, UK

Ashutosh Sharma
Southern Federal University, Russia

Introduction
Technological advancements have improved clinical work management via integral health analysis dramatically. Current developments in artificial intelligence (AI) and machine learning (ML) play a powerful role, changing millions' lives through health, security, and training. These innovations create new potential to promote health, prevent disease and promote healthcare. AI and machine learning can discover and correct uncertainty issues. This is done through uncontrolled analyzes of data and extensive learning approaches. In order to make AI an easier tool in our daily lives, we must use unattended concepts for learning in order to increase the efficiency and precision of health-based systems. However, AI and machine learning models demand efficient extraction and selection algorithms as tools for the preprocessing of medical images. The extraction and selection strategies thereby restrict the performance of medical image analysis based on the machine learning. Many scientists have recently used multimedia models to analyze the medical images. Multimedia models use different filters on each layer to automatically extract and select features. While multimedia models are far superior to other models, training in both time and resources is quite inexpensive. Furthermore, due to the complex background of images, the filters used in multimedia models can extract possible number of features in a reasonable time. Thus, multimedia models have received increased attention in order to analyze medical images. The purpose of this special issue is to illustrate the current development and use of multimedia models in the interpretation of medical images. The objective is to support research and development in biomedical imaging and analytics in this interdisciplinary subject by publishing high-quality research papers, which may substantially influence the future of the medical industries.

Recommended Topics
  • Computer Science
  • Information Technology
  • Electrical & Electronics Engineering
  • Developers
  • Designers


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Multimedia Data Management using Emerging Technologies in Healthcare Applications on or before June 30th, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Gaurav Dhiman
Atulya K. Nagar
Ashutosh Sharma
Guest Editors
International Journal of Reliable and Quality E-Healthcare (IJRQEH)
Email: gdhiman0001@gmail.com; atulya.nagar@hope.ac.uk; ashutosh@sfedu.ru