Biomedical research in the 21st century is undergoing a change from conventional laboratory methods to new digital methods facilitated by the application of high-performance computing and big data analytic methods.

The challenges of big data in biomedical research include big data capturing, analysis, information retrieval, transfer and visualisation, and information privacy protection. The research domains have covered not only the original big data key concepts, i.e. volume, variety, and velocity, but also the relevant technology methods such as healthcare decision making, machine learning, natural language processing, medical knowledge representation, and high throughput data analysis.

This Special Issue aims to provide an international forum for research on the academic frontiers in computational methods for biomedical and healthcare big data. The scope includes the original studies and review articles on biomedical and healthcare big data management, big data search and mining, big data learning and analysis, and ethics and privacy protection.

This Conference Issue is being run in partnership with with IEEE International Conference on Bioinformatics and Biomedicine (BIBM), a premier research conference in bioinformatics and biomedicine, held online from December 9-12 (https://www.ieeebibm.org/BIBM2021/). IEEE BIBM 2021 provides a leading forum for disseminating the latest research in bioinformatics and health informatics. Whilst submissions are invited from all researchers, we particularly welcome full-length articles both from attendees and those that have submitted abstracts and posters for consideration at this conference.

Potential topics include but are not limited to the following:

• Biomedical and health big data management and analytics
• Health big data acquisition, integration, cleaning, and visualization analytics
• Computational modelling, data integration, and large-scale recommenders for medicine
• Mobile Sensor Data to medical knowledge and internet of things (IoT)
• Biomedical and health big data search and mining
• Medical knowledge web search and mining
• Algorithms and systems for biomedical / health big data search
• Semantic-based medical data mining and data pre-processing
• Predictive analytics on biomedical / health big data
• Machine learning and deep learning for biomedical / health big data
• Feature representation learning for biomedical / health big data
• Ethics and privacy in big data of health
• Privacy-preserving for health big data collection/analytics
• Trust management in IoT and other big data systems for biomedicine and healthcare
• High-performance cryptography and de-identification algorithms