skip to main content
10.1145/3336191.3371879acmconferencesArticle/Chapter ViewAbstractPublication PageswsdmConference Proceedingsconference-collections
abstract

Overview of the Health Search and Data Mining (HSDM 2020) Workshop

Published: 22 January 2020 Publication History

Abstract

We present HSDM, a full-day workshop on Health Search and Data Mining co-located with WSDM 2020's Health Day. This event builds on recent biomedical workshops in the NLP and ML communities but puts a clear emphasis on search and data mining (and their intersection) that is lacking in other venues. The program will include two keynote addresses by key opinion leaders in the clinical, search, and data mining domains. The technical program consists of 6 original research presentations. Finally, we will close with a panel discussion with keynote speakers, PC members, and the audience.
This workshop aims to help consolidate the growing interest in biomedical applications of data-driven methods that becomes apparent all over the search and data mining spectrum, in WSDM's spirit of collaboration between industry and academia.

References

[1]
Tim Althoff, Eric Horvitz, Ryen W White, and Jamie Zeitzer. Harnessing the web for population-scale physiological sensing: A case study of sleep and performance. In Proceedings of the 26th international conference on World Wide Web, pages 113--122. International World Wide Web Conferences Steering Committee, 2017.
[2]
John S Brownstein, Clark C Freifeld, and Lawrence C Madoff. Digital disease detection-harnessing the web for public health surveillance. New England Journal of Medicine, 360(21):2153--2157, 2009.
[3]
Steve Chamberlin, Steven Bedrick, Aaron Cohen, Yanshan Wang, Andrew Wen, Sijia Liu, Hongfang Liu, and William Hersh. A Query Taxonomy Describes Performance of Patient-Level Retrieval from Electronic Health Record Data. HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[4]
I Ralph Edwards and Jeffrey K Aronson. Adverse drug reactions: definitions, diagnosis, and management. The lancet, 356(9237):1255--1259, 2000.
[5]
Christopher Flagg, Ophir Frieder, Sean MacAvaney, and Gholam Motamedi. Streaming Gait Assessment for Parkinson's Disease. HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[6]
Soumya Suvra Ghosal, Indranil Sarkar, and Issmail El Hallaou. Lung nodule classification using Convolutional Autoencoder and Clustering Augmented Learning Method (CALM). HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[7]
Richard M Goldberg, John Mabee, Linda Chan, and Sandra Wong. Drug-drug and drug-disease interactions in the ed: analysis of a high-risk population. The American journal of emergency medicine, 14(5):447--450, 1996.
[8]
Nithin Haridas and Yubin Kim. Clustering Large-scale Diverse Electronic Medical Records to Aid Annotation for Generic Named Entity Recognition. HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[9]
David A Jopp and Christopher B Keys. Diagnostic overshadowing reviewed and reconsidered. American Journal on Mental Retardation, 106(5):416--433, 2001.
[10]
Nanon HM Labrie and Peter J Schulz. Exploring the relationships between participatory decision-making, visit duration, and general practitioners' provision of argumentation to support their medical advice: results from a content analysis. Patient education and counseling, 98(5):572--577, 2015.
[11]
J Michael McGinnis, Leigh Stuckhardt, Robert Saunders, Mark Smith, et al. Best care at lower cost: the path to continuously learning health care in America. National Academies Press, 2013.
[12]
Michael J Paul and Mark Dredze. You are what you tweet: Analyzing twitter for public health. In ICWSM 2011, 2011.
[13]
Adam Sadilek, Stephanie Caty, Lauren DiPrete, Raed Mansour, Tom Schenk, Mark Bergtholdt, Ashish Jha, Prem Ramaswami, and Evgeniy Gabrilovich. Machine-learned epidemiology: real-time detection of foodborne illness at scale. npj Digital Medicine, 1(1):36, 2018.
[14]
Adam Sadilek, Henry Kautz, and Vincent Silenzio. Modeling spread of disease from social interactions. In ICWSM 2012, 2012.
[15]
Hanna Suominen, Liadh Kelly, Lorraine Goeuriot, Aurélie Névéol, Lionel Ramadier, Aude Robert, Evangelos Kanoulas, Rene Spijker, Leif Azzopardi, Dan Li, et al. Overview of the clef ehealth evaluation lab 2018. In International Conference of the Cross-Language Evaluation Forum for European Languages. Springer, 2018.
[16]
Amogh Kamat Tarcar, Aashis Tiwari, Dattaraj Rao, Vineet Naique Dhaimodker, Penjo Rebelo, and Rahul Desai. Healthcare NER Models Using Language Model Pretraining. HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[17]
Jan Trienes, Dolf Trieschnigg, Christin Seifert, and Djoerd Hiemstra. Comparing Rule-based, Feature-based and Deep Neural Methods for De-identification of Dutch Medical Records. HSDM 2020 Workshop on Health Search and Data Mining, 1, 2020.
[18]
Justin M Weis and Paul C Levy. Copy, paste, and cloned notes in electronic health records. Chest, 145(3):632--638, 2014.
[19]
Ryen W White, Rave Harpaz, Nigam H Shah, William DuMouchel, and Eric Horvitz. Toward enhanced pharmacovigilance using patient-generated data on the internet. Clinical Pharmacology & Therapeutics, 96(2):239--246, 2014.
[20]
Ryen W White and Eric Horvitz. Evaluation of the feasibility of screening patients for early signs of lung carcinoma in web search logs. JAMA oncology, 3(3):398--401, 2017.
[21]
Elad Yom-Tov, Diana Borsa, Ingemar J Cox, and Rachel A McKendry. Detecting disease outbreaks in mass gatherings using internet data. Journal of medical Internet research, 16(6):e154, 2014.

Cited By

View all
  • (2021)Real Estate Price Prediction using Data Mining Techniques2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON)10.1109/GUCON50781.2021.9573829(1-4)Online publication date: 24-Sep-2021
  • (2021)Decision Support System on Determination of Contraception Tools as an Effort to Suppress the Number of Growth Ratios in IndonesiaRecent Trends in Mechatronics Towards Industry 4.010.1007/978-981-33-4597-3_69(771-778)Online publication date: 16-Jul-2021

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining
January 2020
950 pages
ISBN:9781450368223
DOI:10.1145/3336191
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 January 2020

Check for updates

Author Tags

  1. data mining
  2. healthcare informatics
  3. information retrieval

Qualifiers

  • Abstract

Funding Sources

  • UPMC Enterprises

Conference

WSDM '20

Acceptance Rates

Overall Acceptance Rate 498 of 2,863 submissions, 17%

Upcoming Conference

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2021)Real Estate Price Prediction using Data Mining Techniques2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON)10.1109/GUCON50781.2021.9573829(1-4)Online publication date: 24-Sep-2021
  • (2021)Decision Support System on Determination of Contraception Tools as an Effort to Suppress the Number of Growth Ratios in IndonesiaRecent Trends in Mechatronics Towards Industry 4.010.1007/978-981-33-4597-3_69(771-778)Online publication date: 16-Jul-2021

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media