Guangzhou, December 5, 2020: New journal BIO Integration (BIOI) publishes its third issue, volume 1, issue 3 which is a themed issue on the integration of artificial intelligence (AI) in medicine and biomedicine. BIOI is a peer-reviewed, open access, international journal, which is dedicated to spreading multidisciplinary views driving the advancement of modern medicine. Aimed at bridging the gap between the laboratory, clinic, and biotechnology industries, it will offer a cross-disciplinary platform devoted to communicating advances in the biomedical research field and offering insights into different areas of life science, in order to encourage cooperation and exchange among scientists, clinical researchers, and health care providers.
Featured papers in this issue:
The first featured article in this issue is an opinion article entitled "New Roles for Clinicians in the Age of Artificial Intelligence" by authors Fengyi Zeng, Xiaowen Liang and Zhiyi Chen. Artificial intelligence (AI) has been widely applied in the medical field. Barely a day goes by without a claim that AI techniques are poised to replace most of today's professionals. The integration of AI in medicine has necessitated the exploration of new roles for clinicians in the age of AI.
The second featured article in this issue is a review article entitled "Artificial Intelligence (AI)-aided Disease Prediction" by Chenxi Liu, Dian Jiao and Zhe Liu. Artificial intelligence (AI) used in clinical medicine is witnessing increasing innovations in the fields of AI-aided image analysis, AI-aided lesion determination and AI-assisted healthcare management. This review article focuses on the emerging applications of AI-related medicine and AI-assisted visualized medicine, including novel diagnostic approaches, metadata analytical methods, and versatile AI-aided treatment applications in preclinical and clinical uses, and also looks at future perspectives of AI-aided disease prediction.
The third featured article in this issue is a review article entitled "A Survey on Artificial Intelligence in Chest Imaging of COVID-19" by Yun Chen, Gongfa Jiang, Yue Li, Yutao Tang, Yanfang Xu, Siqi Ding, Yanqi Xin and Yao Lu. Chest imaging techniques including computed tomography and X-ray scans are indispensable tools in COVID-19 diagnosis and its management. The strong infectiousness of this disease brings a huge burden for radiologists. In order to overcome the difficulty and improve accuracy of the diagnosis, artificial intelligence (AI)-based imaging analysis methods are explored. This survey focuses on the development of chest imaging analysis methods based on AI for COVID-19 in the past few months. Imaging analysis methods of two typical viral pneumonias are reviewed, which can provide a reference for studying the disease on chest images.
Other articles published in the issue include:
Scale-aware Auto-context-guided Fetal US Segmentation with Structured Random Forests
Xin Yang, Haoming Li, Li Liu and Dong Ni
News and Views
BIO Integration is a fully open access journal which will allow for the rapid dissemination of multidisciplinary views driving the progress of modern medicine.
As part of its mandate to help bring interesting work and knowledge from around the world to a wider audience, BIOI will actively support authors through open access publishing and through waiving author fees in its first years. Also, publication support for authors whose first language is not English will be offered in areas such as manuscript development, English language editing and artwork assistance.
BIOI is now open for submissions; articles can be submitted online at https:/
Please visit http://www.
Editorial Board: https:/
Submissions may be made using Scholar One.
There are no author submission or article processing fees.