SDM 2018 Workshop on Data Mining for Medicine and Healthcare

SDM 2018 Workshop Proposal

Workshop Title: 7th Workshop on Data Mining for Medicine and Healthcare

Workshop Organizers

Program chairs

Organizer

Affiliation

E-mail

Fei Wang

Cornell University

few2001@med.cornell.edu

Xi Zhang

Cornell University

xiz2016@med.cornell.edu

Lifang He

University of Illinois at Chicago

lifanghescut@gmail.com

 

Workshop Description

In virtually every country, the cost of healthcare is increasing more rapidly than the willingness and the ability to pay for it. At the same time, more and more data is being captured around healthcare processes in the form of Electronic Health Records (EHR), health insurance claims, medical imaging databases, disease registries, spontaneous reporting sites, and clinical trials. As a result, data mining has become critical to the healthcare world. On the one hand, EHR offers the data that gets data miners excited, however on the other hand, is accompanied with challenges such as 1) the unavailability of large sources of data to academic researchers, and 2) limited access to data-mining experts. Healthcare entities are reluctant to release their internal data to academic researchers and in most cases there is limited interaction between industry practitioners and academic researchers working on related problems.

The objectives of this workshop are:

1. Bring together researchers (from both academia and industry) as well as practitioners to present their latest problems and ideas.

2. Attract healthcare providers who have access to interesting sources of data and problems but lack the expertise in data mining to use the data effectively.

3. Enhance interactions between data mining, text mining and visual analytics communities working on problems from medicine and healthcare.

SDM is a unique venue for this workshop as leading researchers and practitioners from academia and industry will be able to participate. A workshop where healthcare professionals can have an audience, present and discuss their problems, views and ideas on the field as well as pose research challenges will attract them to SDM. The organizers of this proposed workshop have continuous and in-depth contact with people working on healthcare applications of data mining and healthcare professionals in the US and Europe which will attract a broad and varied set of participants. We believe that this workshop will serve as a bridge between the traditional SDM community and healthcare professionals - two groups of participants that have a lot to learn from and share with each other.

Content

The organization team and the proposed Program Committee of the workshop, itself, presents a mix from academia and industry. In addition to the more classical data mining approaches, this workshop aims to include two new topic fields – i.e. visual analytics and text mining in medicine and healthcare. By this extension, we aim to foster interactions among multiple communities that work at the intersections of data mining, medicine and healthcare.

Topic areas for the workshop include (but are not limited to) the following:

       Statistical analysis and characterization of healthcare data

       Text mining - mining free text in electronic medical records

       Visual analysis and exploration of longitudinal clinical trial data

       Meaningful use of healthcare data for improved patient care and cost-reduction

       Data quality assessment and improvement: preprocessing, cleaning, missing data treatment etc.

       Pattern detection and hypothesis generation from observational data

       Visualization of prescriptions drugs and interactions

       Privacy and security issues in healthcare

       Information fusion and knowledge transfer in healthcare

       Evolutionary and longitudinal patient and disease models

       Medical fraud detection

       Help with ICD 9 to ICD 10 conversions

       Health Information exchanges

       Hospital readmission analytics

 

Duration of the workshop: full-day workshop

Target Audience: researchers, medical doctors and people from medical and healthcare sector

Preliminary list of potential program committee members that we could possibly contact and invite to participate:

       David Buckeridge, McGill University

       John Holmes, University of Pennsylvania

       Christopher Yang, Drexel University

       Niels Peek, University of Amsterdam

       Ameen Abu-Hanna, Amsterdam University  

       Nitesh Chawla, University of Notre Dame

       Nada Lavrac, Institute Jozef Stefan

       Mykola Pechenitzky, Technical University Eindhoven

       Zoran Obradovic, Temple University

       Jinbo Bi, University of Connecticut

       Heng Huang, University of Texas at Arlington

       Ee-Peng Lim, Singapore Management University

       Haesun Park, Georgia Institute of Technology

       Greg Cooper, Univ. of Pittsburgh School of Medicine

       Jieping Ye, Arizona State University

       Shipeng Yu, Siemens Solutions

       Vikas Sindhwani, IBM T. J. Watson Research Center

       Adam Perer, IBM T.J. Watson Research Center

       Ben Shneiderman, University of Maryland

       Catherine Plaisant, University of Maryland

       Jeff Heer, Stanford University

       Yuval Shahar, Ben Gurion University

       Jesus Caban, NIH

       Robert Kosara, University of North Carolina at Charlotte

       Klaus Mueller, Stony Brook University

       Rayid Ghani, Obama for America

       Jianying Hu, IBM T.J. Watson Research Center

       Balaji Krishnapuram, Siemens Medical Solutions

       Mohit Kumar, Accenture Technology Labs

       David Madigan, Columbia University

       Jonathan Silverstein, NorthShore University HealthSystem

       Jimeng Sun, IBM T.J. Watson Research Center

       K P Unnikrishnan, NorthShore University HealthSystem

       Ramasamy Uthurusamy, General Motors

       John Younger, University of Michigan

       Martijn Schuemie, Erasmus University Medical Center

       Sophia Ananiadou, University of Manchester

       Jin-Dong Kim, Database Center for Life Science

 

Preliminary list of potential keynote speakers that we could possibly contact and invite to participate:

       Xiaoqian Jiang, UCSD

       Zoran Obradovic, Temple

       Peter B. Walker. ONR

       Yang Huang. Shu Rui Tech

Previous editions of the workshop

First Workshop on Data Mining for Medicine and Healthcare was organized at KDD 2011 conference in San Diego, CA. The workshop was implemented as a full-day workshop with 2 invited speakers, 6 full papers and 4 short papers. We estimate the average attendance throughout the day at 40 people. The panel including 5 renowned researchers, CEOs and medical doctors took place after the paper presentations. Keynote lectures and the panel are available at http://videolectures.net/datamining2011_san_diego/.

Second Workshop on Data Mining for Medicine and Healthcare was organized in conjunction with SDM 2013 conference in Austin, TX. The full-day workshop attracted over 50 people throughout the day. We had 4 invited speakers (Joydeep Ghosh, Marc Suchard, Jimeng Sun, Nitesh Chawla) from different fields of data mining with applications in medicine and healthcare.

Third Workshop on Data Mining for Medicine and Healthcare was organized in conjunction with SDM 2014 conference in Philadephia, PA. The full-day workshop attracted over 30 people throughout the day. We had 6 invited speakers (Zoran Obradovic, Christopher Yang, Patrick Ryan, Anastasia Christianson, Chandan Reddy, Zhi Wei) from different fields of data mining with applications in medicine and healthcare.

Fourth Workshop on Data Mining for Medicine and Healthcare was organized in conjunction with SDM 2015 conference in Vancouver, B.C., Canada. The full-day workshop attracted over 30 people throughout the day. We had 4 invited speakers (Dejing Dou, Xiang Zhang, Raymond Ng and Milos Hauskrecht) from different fields of data mining with applications in medicine and healthcare.

Fifth Workshop on Data Mining for Medicine and Healthcare was organized in conjunction with SDM 2016 conference in Miami, FL. The full-day workshop attracted over 30 people throughout the day. We had 3 invited speakers (Mykola Pechenizkiy, Mitsunori Ogihara and Rave Harpaz) from different fields of data mining with applications in medicine and healthcare.

 

Sixth Workshop on Data Mining for Medicine and Healthcare was organized in conjunction with SDM 2017 conference in Houston, TX. The full-day workshop attracted over 30 people throughout the day. We had 2 invited speakers (Genevera Allen and Xiaoning Qian) from different fields of data mining with applications in medicine and healthcare.

 

Short biographies

Fei Wang

Dr. Fei Wang is an Assistant Professor in Division of Health Informatics, Department of Healthcare Policy and Research, Cornell University. His major research interest is data analytics and its applications in health informatics. His papers have received over 5,300 citations so far with an H-index 39. His papers won best paper award in ICHI 2016, best student paper award in ICDM 2015, best research paper nomination for ICDM 2010, Marco Romani Best paper nomination in AMIA TBI 2014, and his paper was selected into the best paper finalist in SDM 2011 and 2015. Dr. Wang is an action editor of the journal Data Mining and Knowledge Discovery, an associate editor of Journal of Health Informatics Research and Smart Health, and an editorial board member of Pattern Recognition and International Journal of Big Data and Analytics in Healthcare. Dr. Wang is the vice chair of the KDD working group in AMIA. More details of Dr. Wang can be found on https://sites.google.com/site/feiwang03/.

 

 

Xi Zhang

 

Dr. Xi Zhang is currently a Postdoctoral Research Associate collaborating with Dr. Fei Wang. She got her PhD from Chinese Academy of Sciences in 2015, followed by one-year working experience at Huawei Noah Arks Lab in 2016. Dr. Zhang joined in Cornell since December 2016. Dr. Zhang has worked extensively on deep learning technologies in information science, especially information retrieval. She has hands on experience on application of data mining technologies in solving healthcare problems. At Weill Cornell, Xi has been working on developing data mining methods for disease subtyping as well as hospital readmission prediction.

 

Lifang He

 

Dr. Lifang He is currently a Postdoctoral Research Associate collaborating with Dr. Philip Yu. She got her PhD from Shenzhen University in China in 2014. Her major research interests are data mining, especially tensor methodologies and their applications in biomedical informatics (especially brain network discovery). She has published 36 papers on top data mining and machine learning venues including ICML, KDD, ICDM, SDM, TKDE, etc.

 

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