Special Issue in Artificial Intelligece for Biomedical Informatics

2020-01-10

Biomedical Informatics is an interdisciplinary field that follows and studies the real uses of biomedical data, knowledge, and information for precise problem solving and decision making, driven by exertions to recover human health. It is a branch of health informatics and evolves with advances in biomedicine, which applies values of natural science, biology, and biochemistry to healthcare and medicine. Informatics in biomedical comprises clinical, consumer health, imaging, research, public health informatics, and health information management. Biomedical informatics will become more reliant on Artificial intelligence with the rise of technology and the extensive digitization of personal health data. It reaches across medical disciplines to uncover disease, provide clinical insights, treatment, medical injury, response patterns, etc. It helps to generate, use, retrieve, store and share data by advance computing as it applies to Biomedicine.

Artificial Intelligence (AI) in the Biomedical environment works by combining large volumes of data with an iterative process and intellectual algorithms though allowing the software to learn automatically from various features or patterns in the data. AI algorithms are trained with thousands of scans and tested information to analyse more quickly, accurately and efficiently than human specialists. These frameworks work with data, information, knowledge and intelligence, descriptive, predictive and perspective functions. An AI technique also facilitates data-driven and evidence-based decision making and it will be complete with identifying health practitioners with appropriate medical information and knowledge. Developing intelligent health systems through biomedical informatics is research areas of AI techniques, where the advances are tackled to real-world healthcare problems.

 

Recent hardware and software advancements are capable of training themselves to intelligent learning process and environment which can influence and improve the overall health. The goal of this special issue on “AI for Biomedical informatics” is to gather the researches based on the latest advancement in biomedical data with the assistance of artificial intelligent. Topics of interest include but are not restricted to: 

  • Design and evaluation of Intelligent Healthcare System using AI
  • Recent advances in Biomedical based information analysis
  • Data mining and knowledge discovery assessment in biomedical informatics
  • Efficient design of AI based algorithms for biomedical informatics
  • Theories on building an intelligent system model for integrative biomedical informatics
  • Designing a new methodologies for biomedical information in clinical traits
  • Opportunities and challenges in data driven health engineering
  • An analytical view on sensing, transfer and storage of biomedical data
  • Future aspects of improving biomedical informatics for real-world Healthcare problems
  • Various applications of AI for Biomedical informatics

 Important dates:

  • Deadline: 25-05-2020 
  • Author notification 15-08-2020 
  • Revised papers submission 15-10-2020 
  • Final Acceptance 20-12-2020

 Guest Editors: 

Dr. Gunasekaran Manogaran, Big Data Scientist, University of California, Davis, USA

Dr. Hassan Qudrat-Ullah, Professor of Decision Sciences, School of Administrative Studies, York University, Toronto, Canada

 Dr.Qin Xin, Full Professor of Computer Science, Faculty of Science and Technology, University of the Faroe Islands,  Faroe Islands.