SDM 2018 Workshop Proposal Workshop Title: 7th Workshop on Data Mining for Medicine and Healthcare Workshop Organizers Program chairs
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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