PHAI-20: The 2020 International Workshop On Pervasive Health With Artificial Intelligence |
Website | https://www.gpc2020.cn/workshops/phai-20.html |
Submission link | https://easychair.org/conferences/?conf=phai20 |
Submission deadline | February 1, 2020 |
With the popularity of smart devices and social media, the emerging artificial intelligence theories and technologies are reshaping the landscape of human health by providing an new approach to pervasive health. The pervasive health is an interdisciplinary field that enables the intelligent systems to sense and mine health states, support smart decisions, maximize the treatment outcomes and facilitate prevention and surveillance based on the ubiquitous ‘digital footprints’ from heterogeneous data sources, e.g. ubiquitous sensors, social media and healthcare systems. Compared with the conventional healthcare industry, AI-enabled pervasive health provides one automated solution to conduct deep and comprehensive analysis for healthcare with efficient and effective diagnosis, personalized therapeutic approaches and early prevention.
The goal of this workshop is to provide a forum for researchers and practitioners to discuss and share their research work associated with AI-enabled human health. We welcome contributions within a broad range of intelligent sensing and computing to foster collaboration and to apply AI and ML to some of the most pressing topics in human health.
Important Dates
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
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Paper Submission Deadline: Feb 1st, 2020
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Authors Notification: March 15th, 2020
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Camera-Ready Paper Due: April 1st 2020
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Conference Date: May 8, 2020
List of Topics
- Data mining and machine learning for pervaisve health
- Explainable models for precise diagnosis
- Causality inference for early prevention
- Information systems for public health
- Analytics for big data related with public health
- Fusion of heterogeneous data
- Pruning and compression of deep learning models
Committees
Program Committee
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Zhu Zhang, Institute of Automation Chinese Academy of Sciences, China
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Qingpeng Zhang, City University of Hong Kong, Hong Kong
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Xiaolong Zheng, Institute of Automation Chinese Academy of Sciences, China
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Xuan wei, University of Arizona, USA
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Sagar Samtani, University of South Florida, USA
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Saike He, Institute of Automation Chinese Academy of Sciences, China
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Fan Wu, Shanghai JiaoTong University, China
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Xiao Liu, Arizona State University, USA
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Helei Cui, Northwestern Polytechnical University, China
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Xiaolin Fang, Southeast University, China
Organizing committee
- Yunji Liang, Northwestern Polytechnical University, China liangyunji@nwpu.edu.cn
Publication
PHAI-20 proceedings will be published by Springer. For the preparation of the camera-ready papers/files, authors have to strictly adhere to the Springer CCIS Authors' Instructions and are strongly encouraged to use the CCIS LaTeX style files or templates. The instructions for authors are available at https://www.springer.com/series/7899
The CCIS series is devoted to the publication of proceedings of computer science conferences. Its aim is to efficiently disseminate original research results in informatics in printed and electronic form. While the focus is on publication of peer-reviewed full papers presenting mature work, inclusion of reviewed short papers reporting on work in progress is welcome, too. Besides globally relevant meetings with internationally representative program committees guaranteeing a strict peer-reviewing and paper selection process, conferences run by societies or of high regional or national relevance are also considered for publication.
CCIS is abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus. CCIS volumes are also submitted for the inclusion in ISI Proceedings.
Venue
The conference will be held in Xi'an, ShaanXi, China
Contact
All questions about submissions should be emailed to liangyunji@nwpu.edu.cn