Projects per year
Brain informatics is a novel interdisciplinary area that focuses on scientifically studying the mechanisms of human brain information processing by integrating experimental cognitive neuroscience with advanced Web intelligence-centered information technologies. Web intelligence, which aims to understand the computational, cognitive, physical, and social foundations of the future Web, has attracted increasing attention to facilitate the study of brain informatics to promote human health. A large number of articles created in the recent few years are proof of the investment in Web intelligence-assisted human health. This study systematically reviews academic studies regarding article trends, top journals, subjects, countries/regions, and institutions, study design, artificial intelligence technologies, clinical tasks, and performance evaluation. Results indicate that literature is especially welcomed in subjects such as medical informatics and health care sciences and service. There are several promising topics, for example, random forests, support vector machines, and conventional neural networks for disease detection and diagnosis, semantic Web, ontology mining, and topic modeling for clinical or biomedical text mining, artificial neural networks and logistic regression for prediction, and convolutional neural networks and support vector machines for monitoring and classification. Additionally, future research should focus on algorithm innovations, additional information use, functionality improvement, model and system generalization, scalability, evaluation, and automation, data acquirement and quality improvement, and allowing interaction. The findings of this study help better understand what and how Web intelligence can be applied to promote healthcare procedures and clinical outcomes. This provides important insights into the effective use of Web intelligence to support informatics-enabled brain studies.
|Early online date||12 Feb 2022|
|Publication status||Published - Feb 2022|
Bibliographical noteFunding Information:
This study has been supported by One-off Special Fund from Central and Faculty Fund in Support of Research from 2019/20 to 2021/22 (MIT02/19-20), Research Cluster Fund (RG 78/2019-2020R), Dean’s Research Fund 2019/20 (IDS-2/2020) of The Education University of Hong Kong, and the Faculty Research Grants (DB21B6 and DB21A9) and the Direct Grant (DR22A2) of Lingnan University, Hong Kong.
© 2022, The Author(s).
- Artificial intelligence
- Cognitive intelligence
- Human health
- Machine intelligence
- Systematic review
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- 1 Finished
Preliminary Study on Deep Learning Techniques for Learning Low-level Visions for All Seasons
XIE, H., LIAO, J. & QIN, J.
1/01/22 → 18/12/22
Project: Grant Research