Call for Papers


  • Paper Submission: Apr 9, 2018
  • Acceptance: Apr 26, 2018
  • Camera-ready: May 24, 2018
  • Conference Dates: Jul 1-3, 2018
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Advances in informatics have led to new opportunities and challenges in healthcare research and applications. There is an increased effort to leverage information systems and data analytics to transform reactive care to proactive and preventive care, clinic-centric practice to patient-centered practice, training-based interventions to globally aggregated evidence, and episodic response to continuous well-being monitoring and maintenance.

International Conference for Smart Health (ICSH), originated in 2013, intends to provide a forum for the growing international smart health research community to discuss the technical, practical, economic, behavioral, and social issues associated with smart health. The 6th International Conference for Smart Health (ICSH 2018) will be hosted by Wuhan University in Wuhan, China on July 1-3, 2018. ICSH 2018 welcomes studies on the principles, approaches, models, frameworks, new applications, and effects of using novel information technology to address healthcare problems and improve social welfare.



The conference proceedings will be published by Springer Lecture Notes in Computer Science (LNCS). Extended versions of selected papers will be considered for publication by IEEE Intelligent Systems (IEEE IS), Electronic Commerce Research and Applications (ECRA), ACM Transactions on Management Information Systems (TMIS), Pacific Asia Journal of the Association for Information Systems (PAJAIS), Global Health Research and Policy (GHRP) and Data and Information Management (DIM).


Topics of Interest:

I. Information Systems for Clinical Practice and Training 

  • EHR Application & Integration
  • Computer-aided Diagnosis
  • Visual Analytics for Healthcare
  • Telehealth Applications
  • IS for Mental Healthcare
  • IS for Patient-centered & Evidence-based Care
  • Virtual Patient Modeling for Training
  • Innovative Design of New Health Information Systems and Clinical Decision Support Tools

II. Clinical and Medical Data Modeling & Analytics 

  • Disease Profiling and Precision Medicine
  • Healthcare Predictive Modeling & Patient Support
  • Text Mining for EHR and Clinical Unstructured Data
  • Information Retrieval for Healthcare Applications
  • Pharmacy Informatics Systems & Drug Discovery
  • Side-effect & Drug Interaction
  • Medical Data Management
  • Data Standards (FHIR, inter-operability, etc.) & Healthcare IT
  • Disease Surveillance & Epidemics Forecasting/Intervention
  • Prediction of Emergent Events with Healthcare Impacts

III. Community, Social Media, and Knowledge Management 

  • Online Patient Communities
  • Online/offline Support Groups
  • IS for Patient Education, Learning and Involvement
  • Role of IS in Patient Data Generation/Collection
  • Healthcare Knowledge Classification and Summarization
  • Health Information Needs, Seeking, Sharing, & Use
  • Social media applications

IV. Smart/Mobile Devices for Healthcare 

  • Assistive Devices for Individuals with Special Needs
  • Mobile / Wearable Devices in Wellness
  • Intelligent Medical Devices & Sensors
  • Continuous Monitoring & Streaming Technologies for Healthcare
  • Virtual & Augmented Reality for Healthcare
  • Computer Support for Surgical Intervention
  • Localized Data for Improving Emergency Care
  • Smart Devices for Healthy Life Styles and Better Self-care

V. Management of Smart Health Systems 

  • Adoption and Use of Clinical Decision Support
  • Adoption and Management of Smart Health Devices
  • Healthcare Workflow Management
  • Real-time Analytics & Optimization in Healthcare Operations
  • Managing the Use of Health IT by Care Providers
  • Privacy, Security & Trust Issues in Health System Use
  • Data Quality of Clinical & Patient-generated Data

VI. Smart Health Business, Social, and Economic Issues 

  • ICT & Health
  • Patient & Physician Engagement & Relationships under IT
  • Impact of Health IT on Small & Rural Communities
  • Impact & Management of IT on Healthcare Access, Costs, Delivery, & Outcomes
  • Accountable Smart Health, Reporting, Pricing, & Auditing
  • Value-based Care & Care Pricing Models
  • New Business Models for Healthcare IT
  • Population Health Management – Clinical & Financial impact
  • Impact of New HIPAA Guidelines on Privacy and Security
  • Meta-studies of Community, National & International Programs


Conference Co-Chairs:

Hsinchun Chen, University of Arizona and Tsinghua University

Qing Fang, Wuhan University

Daniel Zeng, University of Arizona, Chinese Academy of Sciences


  • Paper Submission: Apr 9, 2018
  • Acceptance of the Conference: Apr 26, 2018
  • Deadline for final camera-ready version of accepted papers: May 24, 2018
  • Workshop on the Special Issue: during the Conference
  • Revised Version for the Special Issue: September 1, 2018
  • Acceptance of DIM: October 1, 2018
  • Publishing in DIM: December 31, 2018

Special Issue in the journal of Data and Information Management

Data analysis, information organization, and knowledge discovery in Smart Health

The healthcare industry is facing a golden age of development in the next decade due to ubiquitous computing applications in combination with the use of sophisticated intelligent sensor networks. Efforts have been made to promote the development of intelligent analysis technologies such as real-time health status analysis and health trend analysis based on big data, so as to provide more types of healthcare services to the public. Artificial intelligence provides a new theoretical and technical basis for the rapid development of Smart Health.

In addition to the enormous amounts of daily clinical data, imaging data and laboratory test data from hospitals, mobile devices such as health management wearables and portable wellness monitors produce large amounts of high-dimension, weakly-structured datasets. It becomes crucial to develop effective systems to organize such information. Big data technology provides novel methods to data storage, processing, transferring, and presents unprecedented opportunities to discover new knowledge that will ultimately improve the quality of healthcare. Aside from the growing volume, some types of data such as medical imaging differ in modality, resolution, dimension and quality which introduce new challenges including data integration, mining and analysis. Combining multimodal data from disparate sources will improve diagnosis accuracy and decrease the cost on the clinical level. In big data computing environment, it remains a major challenge to design innovative machine learning algorithms with optimal performance to accommodate the complex big data computing architecture.

In this Special Issue, we would invite authors to contribute high quality research articles and review articles related to the data analysis, information organization, and knowledge discovery in healthcare domain. Potential subjects include but not limited to:

  • Healthcare big data collection, management, sharing methods and tools;
  • Feature selection and machine learning methods for analysis of healthcare big data;
  • Multi-source, multi-modality and heterogeneous healthcare data predictive modeling and patient support;
  • Visualization and interpretation of machine learning based medical imaging analysis results;
  • Information extraction and knowledge discovery from HER or medical literature.

All manuscripts to the Special Issue have to be first submitted to the ICSH with a note “DIM Special Issue” in the title line. The authors of selected manuscripts will attend a workshop on the Special Issue during the Conference. Extended/revised manuscripts will be reviewed for publishing before accepted by DIM (please also check DIM’s CFP at the Conference website).



The International Conference on Smart Health,

Data and Information Management(DIM),


Guest Editors:

Long Lu, PhD


School of Information Management(iSchool)

Wuhan University

Wuhan, China


Neil R. Smalheiser, MD-PhD

Associate Professor

College of Medicine

University of Illinois at Chicago

Chicago, IL, the United States


Fei Wang, PhD

Assistant Professor

Weill Cornell Medical College

Cornell University

New York, NY, the United States