VLDB Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH 2017)
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Gang Luo
Mar 8, 2017, 10:32:04 AM3/8/17
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-- Call for Papers --
The Third International Workshop on Data Management and Analytics
for Medicine and Healthcare (DMAH 2017)
In Conjunction with VLDB 2017
Munich, Germany, September 1, 2017
http://dmah.info/
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 integration for medical data;
Data cleansing for noisy and missing data;
Medical data and knowledge management and decision support;
Data management technologies for medical data;
Semantic Web and ontologies for clinical and biomedical applications;
Medical natural language processing and text mining;
Data mining and knowledge discovery from medical data;
Algorithms to speed up the analysis of big medical data;
Innovative visualization techniques for query and analysis of medical data;
Medical image mining;
Medical information retrieval;
Data privacy and security for healthcare data;
Hospital readmission analytics;
Medical fraud detection;
Social media and Web data analytics for public health;
Data analytics for pervasive computing for medical care.
DMAH 2017 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:
Individual Workshop Papers: May 7, 2017
Notification of Acceptance: June 18, 2017
Camera Ready: July 2, 2017
Workshop date: September 1, 2017
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
Edmon Begoli, Oak Ridge National Laboratory, USA
Program Committee:
Jesús B. Alonso-Hernández, Universidad de Las Palmas de Gran Canaria
Thomas Brettin, Argonne National Laboratory
J. Blair Christian, Oak Ridge National Laboratory
Kerstin Denecke, Bern Univ. of Applied Sciences
Dejing Dou, University of Oregon
Alevtina Dubovitskaya, EPFL
Peter Elkin, University at Buffalo
Vijay Gadapally, Massachusetts Institute of Technology
Zhe He, Florida State University
Guoqian Jiang, Mayo Clinic
Jun Kong, Emory University
Tahsin Kurc, Stony Brook University
Ulf Leser, Humboldt University of Berlin
Yanhui Liang, Stony Brook University
Fernando Martin-Sanchez, Weill Cornell Medicine
Casey Overby, John Hopkins University
Wolfgang Mueller, Heidelberg Institute for Theoretical Studies
Hua Xu, UT Health Science Center
The Third International Workshop on Data Management and Analytics
for Medicine and Healthcare (DMAH 2017)
In Conjunction with VLDB 2017
Munich, Germany, September 1, 2017
http://dmah.info/
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 integration for medical data;
Data cleansing for noisy and missing data;
Medical data and knowledge management and decision support;
Data management technologies for medical data;
Semantic Web and ontologies for clinical and biomedical applications;
Medical natural language processing and text mining;
Data mining and knowledge discovery from medical data;
Algorithms to speed up the analysis of big medical data;
Innovative visualization techniques for query and analysis of medical data;
Medical image mining;
Medical information retrieval;
Data privacy and security for healthcare data;
Hospital readmission analytics;
Medical fraud detection;
Social media and Web data analytics for public health;
Data analytics for pervasive computing for medical care.
DMAH 2017 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:
Individual Workshop Papers: May 7, 2017
Notification of Acceptance: June 18, 2017
Camera Ready: July 2, 2017
Workshop date: September 1, 2017
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
Edmon Begoli, Oak Ridge National Laboratory, USA
Program Committee:
Jesús B. Alonso-Hernández, Universidad de Las Palmas de Gran Canaria
Thomas Brettin, Argonne National Laboratory
J. Blair Christian, Oak Ridge National Laboratory
Kerstin Denecke, Bern Univ. of Applied Sciences
Dejing Dou, University of Oregon
Alevtina Dubovitskaya, EPFL
Peter Elkin, University at Buffalo
Vijay Gadapally, Massachusetts Institute of Technology
Zhe He, Florida State University
Guoqian Jiang, Mayo Clinic
Jun Kong, Emory University
Tahsin Kurc, Stony Brook University
Ulf Leser, Humboldt University of Berlin
Yanhui Liang, Stony Brook University
Fernando Martin-Sanchez, Weill Cornell Medicine
Casey Overby, John Hopkins University
Wolfgang Mueller, Heidelberg Institute for Theoretical Studies
Hua Xu, UT Health Science Center
Gang Luo
Apr 3, 2017, 12:39:50 PM4/3/17
to healthinfor...@googlegroups.com
Kerstin Denecke, Bern Univ. of Applied Sciences
Dejing Dou, University of Oregon
Alevtina Dubovitskaya, EPFL
Peter Elkin, University at Buffalo
Vijay Gadapally, Massachusetts Institute of Technology
Zhe He, Florida State University
Guoqian Jiang, Mayo Clinic
Jun Kong, Emory University
Tahsin Kurc, Stony Brook University
Ulf Leser, Humboldt University of Berlin
Yanhui Liang, Stony Brook University
Fernando Martin-Sanchez, Weill Cornell Medicine
Casey Overby, John Hopkins University
Wolfgang Mueller, Heidelberg Institute for Theoretical Studies
Hua Xu, University of Texas Health Science Center
Dejing Dou, University of Oregon
Alevtina Dubovitskaya, EPFL
Peter Elkin, University at Buffalo
Vijay Gadapally, Massachusetts Institute of Technology
Zhe He, Florida State University
Guoqian Jiang, Mayo Clinic
Jun Kong, Emory University
Tahsin Kurc, Stony Brook University
Ulf Leser, Humboldt University of Berlin
Yanhui Liang, Stony Brook University
Fernando Martin-Sanchez, Weill Cornell Medicine
Casey Overby, John Hopkins University
Wolfgang Mueller, Heidelberg Institute for Theoretical Studies
Gang Luo
Jul 8, 2017, 10:33:14 AM7/8/17
to healthinfor...@googlegroups.com
-- Call for Participation --
This year, we have a rich program covering various topics, including data
privacy and trustability, biomedical data management and integration,
online mining of health related data, and clinical data analytics.
Program:
08:30-10:00 Session 1: Data Privacy and Trustability for Electronic Health
Records
08:30-08:40 Opening remark
08:40-9:30 Keynote I: Health Data Management and Analytics with Privacy and
Confidentiality
(Li Xiong, Emory University, USA)
9:30-10:00 How Blockchain could Empower eHealth: an Application for
Radiation
Oncology
(Alevtina Dubovitskaya, Zhigang Xu, Samuel Ryu, Michael Ignaz
Schumacher
and Fusheng Wang)
10:00-10:30 Coffee Break
10:30-12:00 Session 2: Biomedical Data Management and Integration
10:30-10:55 On-Demand Service-Based Big Data Integration: Optimized for
Research Collaboration
(Pradeeban Kathiravelu, Yiru Chen, Ashish Sharma, Helena
Galhardas,
Peter Van Roy and Luís Veiga)
10:55-11:20 CHIPS – A Service for Collecting, Organizing, Processing, and
Sharing Medical Image Data in the Cloud
(Rudolph Pienaar, Ata Turk, Jorge Bernal-Rusiel, Nicolas Rannou,
Daniel Haehn, P. Ellen Grant and Orran Krieger)
11:20-11:45 High Performance Merging of Massive Data from Genome-Wide
Association Studies
(Xiaobo Sun, Fusheng Wang and Zhaohui Qin)
11:45-12:10 Healthsurance – Mobile App for Standardized Electronic Health
Records Database (Prateek Jain, Sagar Bhargava, Naman Jain, Shelly
Sachdeva, Shivani Batra and Subhash Bhalla)
12:00-13:30 Lunch Break
13:30-15:00 Session 3: Online Mining of Health Related Data
13:30-14:30 Keynote II: Analysis of Online Health-Related User-Generated
Content
(Vagelis Hristidis, University of California, Riverside, USA)
14:30-15:00 Social media mining to understand public mental health
(Andrew Toulis and Lukasz Golab)
15:00-15:30 Coffee Break
15:30-17:00 Session 4: Clinical Data Analytics
15:30-16:00 Effects of varying sampling frequency on the analysis of
continuous
ECG data streams
(Ruhi Mahajan, Rishikesan Kamaleswaran and Oguz Akbilgic)
16:00-16:30 Detection and Visualization of Variants in Typical Medical
Treatment
Sequences
(Yuichi Honda, Muneo Kushima, Tomoyoshi Yamazaki, Kenji Araki and
Haruo Yokota)
16:30-17:00 Umedicine: A System for Clinical Practice Support and Data
Analysis
(Nuno F. Lages, Bernardo Caetano, Manuel J. Fonseca, João D.
Pereira, Helena
Galhardas and Rui Farinha)
17:00: Closing Remarks
privacy and trustability, biomedical data management and integration,
online mining of health related data, and clinical data analytics.
Program:
08:30-10:00 Session 1: Data Privacy and Trustability for Electronic Health
Records
08:30-08:40 Opening remark
08:40-9:30 Keynote I: Health Data Management and Analytics with Privacy and
Confidentiality
(Li Xiong, Emory University, USA)
9:30-10:00 How Blockchain could Empower eHealth: an Application for
Radiation
Oncology
(Alevtina Dubovitskaya, Zhigang Xu, Samuel Ryu, Michael Ignaz
Schumacher
and Fusheng Wang)
10:00-10:30 Coffee Break
10:30-12:00 Session 2: Biomedical Data Management and Integration
10:30-10:55 On-Demand Service-Based Big Data Integration: Optimized for
Research Collaboration
(Pradeeban Kathiravelu, Yiru Chen, Ashish Sharma, Helena
Galhardas,
Peter Van Roy and Luís Veiga)
10:55-11:20 CHIPS – A Service for Collecting, Organizing, Processing, and
Sharing Medical Image Data in the Cloud
(Rudolph Pienaar, Ata Turk, Jorge Bernal-Rusiel, Nicolas Rannou,
Daniel Haehn, P. Ellen Grant and Orran Krieger)
11:20-11:45 High Performance Merging of Massive Data from Genome-Wide
Association Studies
(Xiaobo Sun, Fusheng Wang and Zhaohui Qin)
11:45-12:10 Healthsurance – Mobile App for Standardized Electronic Health
Records Database (Prateek Jain, Sagar Bhargava, Naman Jain, Shelly
Sachdeva, Shivani Batra and Subhash Bhalla)
12:00-13:30 Lunch Break
13:30-15:00 Session 3: Online Mining of Health Related Data
13:30-14:30 Keynote II: Analysis of Online Health-Related User-Generated
Content
(Vagelis Hristidis, University of California, Riverside, USA)
14:30-15:00 Social media mining to understand public mental health
(Andrew Toulis and Lukasz Golab)
15:00-15:30 Coffee Break
15:30-17:00 Session 4: Clinical Data Analytics
15:30-16:00 Effects of varying sampling frequency on the analysis of
continuous
ECG data streams
(Ruhi Mahajan, Rishikesan Kamaleswaran and Oguz Akbilgic)
16:00-16:30 Detection and Visualization of Variants in Typical Medical
Treatment
Sequences
(Yuichi Honda, Muneo Kushima, Tomoyoshi Yamazaki, Kenji Araki and
Haruo Yokota)
16:30-17:00 Umedicine: A System for Clinical Practice Support and Data
Analysis
(Nuno F. Lages, Bernardo Caetano, Manuel J. Fonseca, João D.
Pereira, Helena
Galhardas and Rui Farinha)
17:00: Closing Remarks
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