Artificial Intelligence Meets Medicine: An Interprofessional Perspective for Disease Prediction and Prevention
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).
Deadline for manuscript submissions: closed (4 April 2023) | Viewed by 5197
Special Issue Editors
Interests: blockchain technology and application; swarm intelligence; human-computer interaction; data mining and business intelligence
Interests: pediatrics; clinical epidemiology; medical big data
Interests: supply chain management; sustainability; product deletion
Special Issue Information
Dear Colleagues,
With the increasing amount of data in the biomedical field, how to manage and analyze the data effectively is critical and necessary. The analysis of biomedical information will help to find solutions to global health problems, and even solve problems such as drug design and disease diagnosis and prediction.
Artificial intelligence (AI) technology is increasingly being utilized and adapted into a tool to manage and analyze medical data in a purpose-appropriate manner. Intelligent computing technology, as a booming field, can process biomedical information based on data with an interprofessional perspective, and is able to analyze the impact on disease prediction and prevention.
However, there are still many unresolved theoretical and technical issues in this area that need to be further studied. For example, how can we solve problems in existing systems by using AI? How can we integrate AI tools to assist drug design? How can we use AI for disease prediction and prevention? Are there any ethical issues when deploying AI? As the field evolves, these issues need to be critically examined.
This Special Issue aims to provide an opportunity to exchange ideas and disseminate knowledge within the medical and academic communities. We welcome a variety of technical papers related to bioinformatics, in addition to original research papers and high-quality investigation papers, as well as papers on tools, systems or applications. All papers will be initially reviewed by peer reviewers.
Topics of interest include, but are not limited to:
- Big data analytics methods for biological and medical data,
- Applications using AI and big data analytics based on wearable devices,
- AI methods for biological and medical data,
- AI in COVID-19,
- Analytical tools for biology and medicine,
- Deep learning with MRI, CT, ultrasound and x-ray images,
- Deep learning with multi-semantic image recognition,
- Computer-aided drug design,
- Analysis of biological sequences, structures, and networks,
- AI and aging care system design,
- AI medical robots,
- AI in proactive health and ageing,
- Digital health services for the elderly and large-scale application,
- Chinese medicine knowledge discovery and intelligent decision support,
- Integration and application of Chinese medicine information technology,
- AI in rare disease screening and diagnosis in children.
Dr. Peng Zhu
Dr. Guangjun Yu
Dr. Qingyun Zhu
Dr. Xiang Wu
Guest Editors
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Keywords
- big data
- medical data
- artificial intelligence (AI)
- COVID-19
- deep learning
- digital health
- biological data
- MRI
- CT
- ultrasound
- x-ray images
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