iAIM 2023: International AI in Medicine 2023 Nanyang Technological University Singapore, Singapore, August 5-7, 2023 |
| Conference website | http://iaim2023.sg |
| Submission link | https://easychair.org/conferences/?conf=iaim2023 |
| Submission deadline | June 15, 2023 |
We invite submissions in Artificial Intelligence (AI) for medicine to iAIM 2023, the First International AI in Medicine (iAIM) conference, to be held in Singapore from 5 August to 7 August 2023.
The submission can be a summary of your recent publications related to AI in medicine or novel work reporting significant results on all aspects of AI in medicine. All submissions will be evaluated by the Scientific Committee based on criteria such as originality, significance, soundness, reproducibility, clarity, relevance (to the conference) and quality of presentation. Novel work can be subsequently submitted to any journal for formal publication.
Important Dates
- Paper submission: 1 May 2023
- Author notification: 1 June 2023
- Conference: 5 August - 7 August 2023
All deadlines are at the end of the day specified, anywhere on Earth (UTC-12).
Submission Requirements
Abstracts submitted to iAIM 2023 should be written in English and submitted as a PDF document. Abstracts must be no longer than 2 pages in total, excluding references. Up to 2 accompanying Figures and/or Tables are allowed. Overlength papers will be desk rejected.
Submission URL: Please register and submit your paper at the following link:
https://easychair.org/conferences/?conf=iaim2023
Tracks
iAIM 2023 will feature the following three tracks.
- Artificial Intelligence in Medicine and Health
The AI in Medicine & Health track focuses on theory and practice. There have been recent successes in applying AI in medicine and health, and the landscape of medical AI has matured considerably. Although the widespread use of AI in medicine today is growing, the medical AI community is facing complex and continually evolving ethical, technical, and human-centered challenges.
To promote research in AI in medicine and health, and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of the medical AI community, this track will focus on cutting-edge research that develops novel AI techniques that are poised to broadly reshape today’s medicine. The topics covered by this track include but are not limited to:
- Machine and deep learning approaches for medicine and health
- Human-AI collaboration in medicine and health
- AI-powered applications and systems for medicine and health
- Multimodal medical data processing and mining
- New datasets and benchmarks for medicine and health
- Large (pre-trained) models for medicine and health
- Trustworthiness, explainability, and reliability of AI systems in medicine and health
- Technology in Artificial Intelligence
The Technology in AI track focuses on general AI techniques, including but not limited to AI techniques for medicine and health. Submissions reporting research that advances artificial intelligence are welcomed. The scope includes most areas of AI such as machine learning, computer vision, natural language processing, data mining, planning, and multiagent learning and systems. Works that explore the possibility of applying novel AI algorithms, methods, and ideas to medicine and health are particularly encouraged.
- Ethics and Social Sciences
Recent developments in the field of AI applied to medicine and health has demonstrated the promise of solving many of the existing global issues in advancing human health and managing global health challenges. However, the underlying ethical, legal, and social implications are deserved equal attention in the development and implementation of AI-powered applications and systems for medicine and health.
The Ethics & Social Sciences track focuses on the exploration of the ethical, legal, and social impacts of AI applied to medicine and health, and solutions that address related challenges faced by the medical AI community, such as the regulatory issues regarding the deployment of AI models for healthcare, shifts in responsibility between human and AI systems, ethical data collection and use, and risk of prejudice regarding racial categories.
Inquiries
Please send any inquiries to the iAIM 2023 Scientific Committee:
- Xiuyi Fan (xyfan@ntu.edu.sg)
- Stefano Perna (stefano.perna@ntu.edu.sg)