Smart Health + DiabeticLink Research

Overview

A major goal for healthcare-related IT is to develop trusted healthcare systems that offer relevant decision support to clinicians and patients, and in particular, provide “just in time, just for me” advice at the point of care. In these integrative research projects, we have developed advanced data, text, and web mining algorithms and other computational techniques to process healthcare big data, to provide patient care decision support, and to enable socially-enhanced patient empowerment. We are leveraging our research team members’ computational and social science experience, and extensive healthcare knowledge, by taking a data-centric and cyber community-oriented approach. 

DiabeticLink

DiabeticLink is an intelligent diabetes self-management website that provides a one-stop solution for all diabetes related issues. The website provides content mashup (news, videos, blogs) from credible diabetes related websites, a unique risk engine to predict risk of hospitalization in diabetics, online tracking and enhanced visualization of tracked data and a community feature where people with similar issues can connect. This system is aimed at improving health outcomes among diabetics.

Our specific research objectives were three-fold: (1) developing technical approaches to support cyber-enabled patient empowerment; (2) developing personalized healthcare and community mapping techniques; and (3) conducting theory-driven assessment and evaluation research.

To achieve the first research objective, this project aimed at: (a) developing domain-dependent text processing techniques to extract symptom-disease-treatment information in health-related social media with high precision, (b)  developing novel sentiment analysis techniques suitable for extracting the emotional responses associated with health-related social media content, and (c) developing evolutionary topic detection techniques for patient community question-answering. Accomplishing the second research objective, we developed computational techniques to identify participant interaction networks in social media sites, developed community mapping and visualization techniques for health social media contents, and created a diabetes patient portal system for finding similar patients and mapping the patient community as part of patient empowerment. To evaluate the proposed research, the third research objective, we implemented a cloud-based mobile app to access DiabeticLink and performed multi-stage patient-group field evaluation studies.

Project Summary: DiabeticLink

SilverLink

The aging of the population has become a pressing societal challenge facing many developed and emerging countries, including the U.S. (the aging baby boomers) and China (the reverse 4-2-1 family pyramid due to the former one-child policy). Despite failing health, most senior citizens prefer to live independently at home and hence the focus of current healthcare technologies has shifted from traditional clinical care to "at-home" care for senior citizens. The patent-pending (in both the U.S. and China) SilverLink system is unique in its smart and connected technologies and service model including: (1) affordable and non-invasive home-based mobile health technologies with wearable human and object activity sensors for monitoring health-related motion and daily activities and cost-effective pre-configured home gateway via BLE (Bluetooth Low Energy) and 3G communication; (2) advanced mobile health analytics algorithms for fall detection, health progression monitoring, and patient health anomaly detection and alert in a cloud-based data center; and (3) comprehensive patient health activity portal and support for reporting user activity and health status and engaging with family members.

SilverLink is a smart and connected home monitoring system for senior care which enables affordable connected care for the older population (often with chronic conditions) living independently at home. The system includes affordable and non-invasive home-based mobile health technologies, advanced mobile health analytics algorithms, and comprehensive patient health activity portal and support.

SilverLink has great commercialization potential considering the growing aging population with a need to “age-in-place,” the pressure on hospitals/healthcare providers to reduce rates of readmission (given the high penalty imposed by the US government), current market deficits (lacking affordable but smart health analytics and remote care devices)

Project Summary: SilverLink

Funding (Selected)

We thank the following agencies and companies for providing research funding support:

Caduceus Intelligence Corporation (CIC),through funding provided by the National Science Foundation (NSF):

  • Subcontract from Caduceus Intelligence Corporation, "STTR Phase I: Advanced Analytics for Health Progression Monitoring and Fall Detection in a Novel Home Health Monitoring System," $87,073 (From NSF award IIP-1622788 to Caduceus Intelligence Corporation), July 1, 2016 - June 30, 2017.
  • Subcontract from Caduceus Intelligence Corporation, "STTR Phase I:  The Development and Evaluation of an Intelligent Diabetes Self-Management Tool," $85,354 (From NSF award IIP-1417181 to Caduceus Intelligence Corporation), June 3, 2014 - June 30, 2015.

Taiwan National Science Council. "Taiwan Smart Health Cloud," July 2012-December 2014.

Danish NSF with South Denmark University. "Patients@Home: Innovative Welfare Technology for the 21st Century,” August 2012-July 2015.

NSF, REU (Research Experience for Undergraduates). "A National Center of Excellence for Infectious Disease Informatics,” April 2010-September 2010.

NSF, Information Technology Research (ITR) Program. ""A National Center of Excellence for Infectious Disease Informatics” (IIS-0428241), August 2004-July 2009.

NSF, REU (Research Experience for Undergraduates). "BioPortal Research,” April 2008-July 2009.

 Team Members

Project Collaborators

Publications

Journal Articles

  • W. Shang, H. Chen, and C. Livoti “Adverse Drug Reaction Early Warning Using User Search Data,” Online Information Review, Volume 41, Issue 4, Pages 524-536, 2017.
  • Y. Lin, H. Chen, R. Brown, and S. Li, “Healthcare Predictive Analytics for Risk Profiling in Chronic Care: A Bayesian Multi-Task Learning Approach,” MIS Quarterly, Volume 41, Number 2, Pages 473-495, June 2017.
  • X. Li, T. Zhang, L. Song, Y. Zhang, G. Zhang, C. Xing, and H. Chen, “Effects of Heart Rate Variability Biofeedback Therapy on Patients with Poststroke Depression: A Case Study,” Chinese Medical Journal, Volume 128, Number 18, Pages 2542-2545, 2016.
  • X. Liu and H. Chen, “A Research Framework for Pharmacovigilance in Health Social Media: Identification and Evaluation of Patient Adverse Drug Event Reports,” Journal of Biomedical Informatics, Volume 58, Pages 268-279, 2015.
  • B. Wu, S. Jiang, and H. Chen, “Modeling the Dynamics of Medical Information Through Web Forums in Medical Industry,” Technological Forecasting and Social Change, Volume 97, Pages 77-90, 2015.
  • X. Liu and H. Chen, “Identifying Adverse Drug Events from Patient Social Media: A Case Study of Diabetes,” IEEE Intelligent Systems, Volume 30, Number 3, Pages 44-51, 2015.
  • Y. C. Ku, C. Chao, Y. Zhang, and H. Chen, “Text Mining Self-disclosing Health Information for Public Health Service,” Journal of the American Society for Information Science and Technology, Volume 65, Number 5, Pages 928-947, 2014.
  • Y. Lin, H. Chen, R. Brown, S. Li, and H. Yang, “Time-to-Event Predictive Modeling for Chronic Conditions using Electronic Health Records,” IEEE Intelligent Systems, Volume 29, Number 3, Pages 14-21, 2014.
  • G. Leroy, H. Chen, and T. Rindflesch, "Smart and Connected Health," IEEE Intelligent Systems, Volume 29, Number 3, Pages 2-5, 2014.
  • Y. Li, H. Chen, and R. Brown, "MedTime: A Temporal Information Extraction System for Clinical Narratives," Journal of Biomedical Informatics (46, Supplement), Pages S20-S28, 2013.
  • Y K. Lin, R. A. Brown, and H. Chen, “MedTime: A Temporal Information Extraction System for Clinical Narratives,” Proceedings of the 2012 i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data, Chicago, IL, USA: i2b2, 2012 (MedTime ranked #4 among 12 entries).
  • H. Chen, “Smart Health and Wellbeing,” IEEE Intelligent Systems, Volume 26, Number 5, Pages 78-79, September/October, 2011
  • H. Chen, D. Zeng, and P. Yan, Infectious Disease Informatics: Syndromic Surveillance for Public Health and Biodefense, Springer, 2010. (translated into Chinese, 2011)
  • Y. Chen, S. Brown, P. J. Hu, and H. Chen, “Managing Emerging Infectious Diseases with Information Systems: Reconceptualizing Outbreak Management through the Lens of Loose Coupling,” Information Systems Research, Volume 22, Number 3, Pages 447-468, September 2011.
  • N. Suakkaphong, Z. Zhang, and H. Chen, “Disease Named Entity Recognition using Semisupervised Learning and Conditional Random Fields,” Journal of the American Society for Information Science and Technology, Volume 62, Number 4, Pages 727-737, 2011.
  • D. Zeng, H. Chen, C. Castillo-Chavez, W. B. Lober, and M. Thurmond (Eds.), Infectious Disease Informatics and Biosurveillance, Springer, 2010.
  • X. Li, H. Chen, J. Li, and Z. Zhang, “Gene Function Prediction with Gene Interaction Networks: A Context Graph Kernel Approach Relations,” IEEE Transactions on Information Technology in Biomedicine, Volume 14, Number 1, Pages 119-128, 2010.
  • H. Chen, S. F. Fuller, C. Friedman, and W. Hersh (Eds.), Medical Informatics: Knowledge Management and Data Mining in Biomedicine, Springer, 2005.

Conference Papers

  • X. Liu, B. Zhang, A. Susarla, R. Padman, and H.Chen, “Improving YouTube Self-case Video Search: A Deep Learning Approach for Patuent Knowledge Extraction,” Proceedings of the 2015 Workshop on Information Technologies and Systems (WITS), Dallas, Texas, December 12-13, 2015.
  • X. Liu and H. Chen, “Identifying Novel Adverse Drug Evens from Health Social Media Using Distant Learning,” American Medical Informatics Association (AMIA) 2015 Annual Symposium, San Francisco, November 14-18, 2015.
  • Y. Zhang, Y. Zhang, J. Xu, C. Xing, and H. Chen, “Sentiment Analysis on Chinese Health Forums: A Preliminary Study of Different Language Models,” International Conference on Smart Health, ICSH 2015, Phoenix, Arizona, November 2015. Proceedings. Lecture Notes in Computer Science 8549, Springer 2015.
  • Y. Zhang, Y. Zhang, Y. Yin, J. Xu, C. Xing, and H. Chen, “Chronic Disease Related Entity Extraction in Online Chinese Question & Answer Services,” International Conference on Smart Health, ICSH 2015, Phoenix, Arizona, November 2015. Proceedings. Lecture Notes in Computer Science 8549, Springer 2015.
  • J. Chuang, L. Maimoon, S. Yu, H. Zhu, C. Nybroe, O. Hsiao, U. S. Li, H. Lu, and H. Chen, “SilverLink: Smart Home Health Monitoring for Senior Care,” International Conference on Smart Health, ICSH 2015, Phoenix, Arizona, November 2015. Proceedings. Lecture Notes in Computer Science 8549, Springer 2015.
  • G. Samtani, L. Maimoon, J. Chuang, C. Nybroe, X. Liu, U. Wiil, S. Li, and H. Chen, “DiabeticLink: An Internationally Collaborative Cyber-Enabled Empowerment Platform,” International Conference on Smart Health, ICSH 2015, Phoenix, Arizona, November 2015. Proceedings. Lecture Notes in Computer Science 8549, Springer 2015.
  • X. Chen, Y. Zhang, J. Xu, C. Xing, and H. Chen, “Health-related Spammer Detection on Chinese Social Media,” International Conference on Smart Health, ICSH 2015, Phoenix, Arizona, November 2015. Proceedings. Lecture Notes in Computer Science 8549, Springer 2015.
  • J. Chuang, O. Hsiao, P. Wu, J. Chen, X. Liu, H. De La Cruz, S. Li, and H. Chen, “DiabeticLInk: An Integrated and Intelligent Cyber-enabled Health Social Platform for Diabetic Patients,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • X. Li, T. Zhang, L. Song, Y. Zhang, C. Xing, and H. Chen, “A Control Study on the Effects of HRV Biofeedback Therapy in Patients with Post-stroke Depression,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • X. Song, S. Jiang, X. Yan, and H. Chen, “Collaborative Friendship Betworks in Online Healthcare Communities: An Exponential Random Graph Model Analysis,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • Y. Yin, Y. Zhang, X. Liu, Y. Zhang, C. Xing, and H. Chen, “HealthQA: A Chinese QA Summary System for Smart Health,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • X. Liu, J. Liu, and H. Chen, “Identifying Adverse Drug Events from Health Social Media: A Case Study on Heart Disease Discussion Forums,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science  8549, Springer 2014.
  • X. Chen, Y. Zhang, C. Xing, X. Liu, and H. Chen, “Diabetes-related Topic Detection in Chinese Health Websites Using Deep Learning,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • S. Yu, H. Zhu, S. Jiang, and H. Chen, “Emoticon Analysis for Chinese Health and Fitness Topics,” International Conference on Smart Health, ICSH 2014, Beijing, China, July 2014. Proceedings. Lecture Notes in Computer Science 8549, Springer 2014.
  • X. Liu and H. Chen, “AZDrugMiner: An Information Extraction System for Mining Patient-Reported Adverse Drug Events in Online Patient Forums,” International Conference on Smart Health, ICSH 2013, Beijing, China, August 2013. Proceedings. Lecture Notes in Computer Science 8040, Springer 2013.
  • H. Chen, S. Compton, and O. Hsiao, “DiabeticLink: A Health Big Data System for Patient Empowerment and Personalized Healthcare,” International Conference on Smart Health, ICSH 2013, Beijing, China, August 2013. Proceedings. Lecture Notes in Computer Science 8040, Springer 2013.
  • Y K. Lin, R. A. Brown, and H. Chen, "MedTime: A Temporal Information Extraction System for Clinical Narratives," Proceedings of the 2012 i2b2, 2012 (Medline ranked #4 among 12 entries in i2b2 competition).
  • C. Yang, H. Chen, H. Wactlar, C. Combi, and X. Tang, SHB 2012: International Workshop on Smart Health and Wellbeing. ACM International Conference on Information and Knowledge Management,(CIKM), Hawaii, October 29-November 2, 2012.
  • Y. Ku, C. Chiu, Y. Zhang, L. Fan, and H. Chen, “Global Disease Surveillance using Social Media: HIV/AIDS Content Intervention in Web Forums,” Proceedings of 2010 IEEE International Conference on Intelligence and Security Informatics, ISI 2010, Vancouver, Canada, May 2010.

 

Photo of healthcare technology and doctors courtesy Shutterstock.