Manuscript Topics

With the rapid growth of information technology, the processing of massive health and medical data utilizing advanced information technologies is of great need. Biomedical and health information processing and analysis is one of the most important tasks in the fields of life science and medicine. It has been attracted more and more attentions, and many computational approaches have been developed. There are two main topics in Biomedical and health information processing and analysis: medical data mining, and bioinformatics. For medical data mining, its aim is to utilize information technologies (such as text mining, natural langue processing, image processing, data mining, machine learning, intelligent decision support systems, ontologies, mobile technologies, etc.) to manage and reuse health data. Unstructured data is converted into structured data, information of interest is extracted, and knowledge is discovered and well visualized through these techniques.

For bioinformatics, to expedite analyses of increasing number of biological sequences, many machine-learning algorithms have been introduced into computational biology. By using these techniques, protein structures and functions can be identified based on their primary sequences, and genomics functions can also be analyzed via the sequence data, such as promoter identification, enhancer identification, and disease relationship prediction, etc.

To that end, we would like to invite contributions for the special issue on the topic of "Biomedical and Health Information Processing and Analysis", which will be published in Mathematical Biosciences and Engineering (MBE)" in 2020. We invite submissions for a special issue of Mathematical Biosciences and Engineering focused on information processing technologies applied in healthcare and medical fields. This special issue aims to provide a collection of emerging theories, cutting-edge methodologies, and novel technologies that enable research and application in health information processing for efficient clinical decision making and effective health service delivery. In this call, we focus on sharing recent advances in algorithms and applications that involve combining multiple sources of health information.

Possible topics include, but are not limited to:

• Computational health information analysis
• Deep learning for health and medicine
• Next-generation health information processing technologies
• Using novel data sources (e.g., patient self-reported data, case reports, social media, or clinical research data) for clinical decision making
• Multi-modality combining data, text, videos, images, sound, gene, signals, etc.
• Cross modality learning
• Applications of multimodal learning in medical areas
• Integrating multiple data or knowledge sources for medical knowledge engineering
• Standards-based representation, sharing, and reuse of machine learning algorithms for health information processing
• Clinical image informatics

This special issue is in cooperation with the 2019 China Health information Processing conference (http://cips-chip.org.cn/home) and also beyond it. It is dedicated to cover the related topics on technological advancements for biomedical and health information processing and analysis with focus on data science and machine learning. Only original research contributions will be considered.

Instructions for authors
https://www.aimspress.com/mbe/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
http://oeps.aimspress.com/mbe/ch/author/login.aspx