Connectionists: VLDB Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH 2020)

[GANG LUO]

                       -- Call for Papers --       
	
   The Sixth International Workshop on Data Management and Analytics 
                    for Medicine and Healthcare (DMAH 2020)     
                   In Conjunction with VLDB 2020
                         Tokyo, Japan
		      September 04, 2020
          https://sites.google.com/site/vldbdmah2020/

Healthcare enterprises are producing large amounts of data through electronic medical records, medical imaging, health insurance claims, surveillance, and others. Such data have high potential to transform current healthcare to improve healthcare quality and prevent diseases, and advance biomedical research. Medical Informatics is an interdisciplinary field that studies and pursues the effective use of medical data, information, and knowledge for scientific inquiry, problem solving and decision making, driven by efforts to improve human health and well being.

The goal of the workshop is to bring people in the field cross-cutting information management and medical informatics to discuss innovative data management and analytics technologies highlighting end-to-end applications, systems, and methods to address problems in healthcare, public health, and everyday wellness, with clinical, physiological, imaging, behavioral, environmental, and omic- data, and data from social media and the Web. It will provide a unique opportunity for interaction between information management researchers and biomedical researchers for the interdisciplinary field. 


This workshop welcomes papers that address fundamental research issues for complex medical data environments, data management and analytical methods, systems and applications. 

Topics of interest include, but not limited to:

Big data management for medical data; 
Blockchain for healthcare;         
Biomedical data integration;
Biomedical knowledge management and decision support; Semantics and interoperability for healthcare data; Clinical natural language processing and text mining; Predictive modeling for diagnosis and treatment; Visual analytics for medical data; Medical image analytics; Data privacy and security for healthcare data; Hospital readmission analytics; Medical fraud detection; Social media and Web data analytics for public health (public health 2.0); Data analytics for pervasive computing for medical care.  


DMAH 2020 accept two types of papers: 
1) Regular research papers reporting original research results or significant 
   case studies (18 pages).
2) Extended abstracts presenting novel research directions or challenging 
   problems (4 pages). 


Important Dates:

Abstract (optional): May 29, 2020
Individual Workshop Papers: June 5, 2020 Notification of Acceptance: July 3, 2020 Camera Ready: July 10, 2020 Workshop date: September 04, 2020

All submitted papers will be rigorously reviewed. All accepted papers will be made available as a workshop proceedings to be published by Springer LNCS.

Workshop Chairs:
   Fusheng Wang, Stony Brook University, USA
   Gang Luo, University of Washington, USA
   Alevtina Dubovitskaya, Lucerne University 
     of Applied Sciences and Arts and Swisscom, Switzerland
   Jun Kong, Georgia State University, USA

Program Committee

Edmon Begoli, Oak Ridge National Laboratory, USA Yang Cao, Kyoto University, Japan Blair Christian, Oak Ridge National Laboratory, USA Dejing Dou, University of Oregon, USA Alevtina Dubovitskaya, Lucerne University of Applied Sciences and Arts and Swisscom, Switzerland Peter Elkin, University at Buffalo, USA
Zhe He,	Florida State University, USA
Vagelis Hristidis, University of California-Riverside, USA Athirai Irissappane, University of Washington, USA
Guoqian	Jiang,	Mayo Clinic College of Medicine, USA
Jun Kong, Georgia State University, USA
Tahsin Kurc, Stony Brook University, USA Yanhui Liang, Google Inc., USA Gang Luo, University of Washington, USA Ye Ye, University of Pittsburgh, USA Rui Zhang, University of Minnesota, USA