NLP4Health

Publications

  1. Peer-Reviewed Journal and Conference Publications
  2. Peer-Reviewed Workshop Publications
  3. Peer-reviewed Abstracts
  4. Non Peer-Reviewed Publications
  5. Book Chapters
  6. Tutorial Abstracts
  7. Other Abstracts

Peer-Reviewed Journal and Conference Publications

  • Li J, Yang Y, Wu Z, Vydiswaran VGV, Xiao C. ChatGPT as an attack tool: Stealthy textual backdoor attack via blackbox generative model trigger. In Proceedings of the 24th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) 2024. In print.
  • Ritchie O, Koptyra E, Marquis LB, Kadri R, Laurie A, Vydiswaran VGV, Li J, Brown LK, Veinot TC, Buis L, Guetterman TC. Virtual care: Perspectives from family physicians. Family Medicine. In print.
  • Bhogal AN, Berrocal VJ, Romero DM, Willis MA, Vydiswaran VGV, Veinot TC. Social acceptability of health behavior posts on social media: An experiment. Am J Prev Med 2024 Jan 6:S0749-3797(24)00001-1. PMID:38191003 DOI: 10.1016/j.amepre.2024.01.002. In print.
  • Vydiswaran VGV, Strayhorn A, Weber K, Stevens H, Mellinger J, Winder GS, Fernandez AC. Automated-detection of risky alcohol use prior to surgery using natural language processing. Alcohol: Clinical and Experimental Research (Alcohol Clin Exp Res). 2024 Jan:48(1);153–163. doi: 10.1111/acer.15222 
  • Yu D, Stidham RW, Vydiswaran VGV. A systematic temporal extraction pipeline for medical concepts in clinical notes. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2023.
  • Wu Z, Xiao C, Vydiswaran VGV. HiCL: Hierarchical contrastive learning of unsupervised sentence embeddings. In Findings of the Association for Computational Linguistics: EMNLP 2023.
  • Joo H, Mathis MR, Tam M, James C, Han P, Mangrulkar RS, Friedman CP, Vydiswaran VGV. Applying artificial intelligence and guidelines to assist medical students in recognizing patients with heart failure: Protocol for a randomized trial. JMIR Research Protocols (JMIR Res Protoc). 2023 Oct 24:12:e49842. PMID: 37874618 doi: 10.2196/49842
  • Buis LR, Brown LK, Plegue MA, Kadri R, Laurie AR, Guetterman TC, Vydiswaran VGV, Li J, Veinot TC. Identifying inequities in video and audio telehealth services for primary care encounters during COVID-19: a repeated cross-sectional observational study. J Med Internet Res. 2023 Sep 29:25:e49804. doi: 10.2196/49804 PMID: 37773609 PMCID: PMC10544805.
  • Wu DTY, Hanauer D, Murdock P, Vydiswaran VGV, Mei Q, Zheng K. Developing a semantically based query recommendation for an electronic medical record search engine: Query log analysis and design implications. JMIR Form Res 2023 Sep 15;7:e45376 doi: 10.2196/45376 PMID: 37713239
  • Guetterman TC, Koptyra E, Richie O, Marquis L, Kadri R, Laurie A, Vydiswaran VGV, Li J, Brown LK, Veinot TC, Buis LR. Equity in virtual care: A mixed methods study of perspectives from physicians. J Telemed Telecare 2023 Aug 28:1357633X231194382. doi: 10.1177/1357633X231194382. PMID: 37641207
  • Walling AM, Pevnick J, Bennett AV, Vydiswaran VGV, Ritchie CS. Dementia and electronic health record phenotypes: a scoping review of available phenotypes and opportunities for future research. J Am Med Inform Assoc. 2023 Jun 20;30 (7):1333–48. doi: 10.1093/jamia/ocad086 PMID: 37252836 PMCID: PMC10280354
  • Mahmoudi E, Wu W, Najarian C, Aikens J, Bynum J, Vydiswaran VGV. Identifying Caregiver Availability Using Medical Notes With Rule-Based Natural Language Processing: Retrospective Cohort Study. JMIR Aging. 2022 Sep 22;5(3):e40241. doi: 10.2196/40241. PMID: 35998328; PMCID: PMC9539648.
  • Weissenbacher D, O’Connor K, Rawal S, Zhang Y, Tsai RT, Miller T, Xu D, Anderson C, Liu B, Han Q, Zhang J, Kulev I, Köprü B, Rodriguez-Esteban R, Ozkirimli E, Ayach A, Roller R, Piccolo S, Han P, Vydiswaran VGV, Tekumalla R, Banda JM, Bagherzadeh P, Bergler S, Silva JF, Almeida T, Martinez P, Rivera-Zavala R, Wang C, Dai H, Hernandez LAR, Gonzalez-Hernandez G. Automatic extraction of medication Mentions from Tweets – Overview of the BioCreative VII Shared Task 3 Competition. Database. 2023 Feb;2003:baac108. Oxford Publ. doi: 10.1093/database/baac108 PMID: 36734300
  • Yu D, Vydiswaran VGV. Assessment of mentions of adverse drug events in social media through natural language processing. JMIR Med Inform. 2022 Sep 28;; 10(9): e38140. doi: 10.2196/38140. PMCID: PMC9557755 PMID: 36170004.
  • Han P, Fu S, Kolis J, Hughes R, Hallstrom BR, Carvour M, Maradit-Kremers H, Sohn S, Vydiswaran VGV. Multi-center validation of natural language processing algorithms for the detection of common data elements in operative notes for total hip arthroplasty: Algorithm development and validation. JMIR Med Inform. 2022 Aug 31;10(8):e38155. doi: 10.2196/38155 PMCID: PMC9475406 PMID: 36044253.
  • Veinot TC, Clarke PJ, Romero DM, Buis LR, Dillahunt TR, Vydiswaran VGV, Beals A, Brown L, Richards O, Williamson A, Antonio MG. Equitable research PRAXIS: A framework for health informatics methods. Yearb Med Inform 2022 Aug; 31(1):307-316 PMID: 36463889 PMCID: PMC9719773 doi: 10.1055/s-0042-1742542. Epub 2022 Dec 4.
  • Li J, Wu Z, Ping W, Xiao C, Vydiswaran VGV. Defending against insertion-based textual backdoor attacks via attribution. In Findings of the Association for Computational Linguistics: ACL 2023. 2023 Jul, pages 8818–33. https://aclanthology.org/2023.findings-acl.561
  • Stidham RW, Yu D, Zhao X, Bishu S, Rice M, Bourque C, Vydiswaran VGV. Identifying the presence, activity, and status of extraintestinal manifestations of inflammatory bowel disease using natural language processing of clinical notes. Inflamm Bowel Dis. 2022 Jun 3;izac109. doi: 10.1093/ibd/izac109. PMID: 35657296
  • Wu Z, Wang S, Gu J, Hou R, Dong Y, Vydiswaran VGV, Ma H. IDPG: An instance-dependent prompt generation method. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2022), pages 5507–21. doi: 10.18653/v1/2022.naacl-main.403
  • Singh K, Murali M, Stevens H, Vydiswaran VGV, Bohnert A, Brummett CM, Fernandez AC. Predicting persistent opioid use after surgery using electronic health record and patient-reported data. Surgery. 2022 Feb 15;S0039-6060(22)00013-7. DOI: 10.1016/j.surg.2022.01.008. PMID: 35181126
  • McCreedy E, Gilmore-Bykovskyi A, Dorr DA, Lima J, McCarthy EP, Meyers DJ, Platt R, Vydiswaran VGV, Bynum JPW. Barriers to identifying residents with dementia for embedded pragmatic trials: a call to action. Journal of the American Geriatrics Society 2022 Feb;70(2):638-641. DOI: 10.1111/jgs.17539. Epub 2021 Nov 2. PMID: 34727369 PMCID: PMC8821246
  • Joo H, Burns M, Kalidaikurichi Lakshmanan SS, Hu Y, Vydiswaran VGV. Neural machine translation-based automated Current Procedural Terminology classification system using procedure text: Development and validation study. JMIR Form Res 2021;5(5):e22461 DOI: 10.2196/22461 PMID: 34037526 PMCID: 8190648
  • Chang T, DeJonckheere M, Vydiswaran VGV, Li J, Buis LR, Guetterman TC. Accelerating mixed methods research with natural language processing of big text data. Journal of Mixed Methods Research. DOI: 10.1177/15586898211021196
  • Lester CA, Ding Y, Li J, Jiang Y, Rowell B, Vydiswaran VGV. Human versus machine translation of electronic prescription directions. Journal of the American Pharmacists Association (J Am Pharm Assoc (2003)). 2021 Feb 19;S1544-3191(21)00074-1. PMID: 33766549 DOI: 10.1016/j.japh.2021.02.006.
  • Zhao X, Vydiswaran VGV. LIREx: Augmenting language inference with relevant explanations. In Proceedings of the Thirty-fifth AAAI Conference on Artificial Intelligence (AAAI), 2021:35(16);14532–9. https://ojs.aaai.org/index.php/AAAI/article/view/17708
  • Li J, Murali A, Mei Q, Vydiswaran VGV. Re-ranking biomedical literature for precision medicine with pre-trained neural models. In Proceedings of the IEEE International Conference of Healthcare Informatics (ICHI), 2020, pp. 1-3. DOI: 10.1109/ICHI48887.2020.9374401
  • Li J, Lester C, Zhao X, Ding Y, Jiang Y, Vydiswaran VGV. PharmMT: A neural machine translation approach to simplify prescription directions. In Findings of the Association for Computational Linguistics: EMNLP 2020; pp. 2785–96. DOI: 10.18653/v1/2020.findings-emnlp.251
  • Bynum JPW, Dorr DA, Lima J, McCarthy EP, McCreedy E, Platt R, Vydiswaran VGV. Using healthcare data in embedded pragmatic clinical trials among people living with dementia and the caregivers: state-of-the-art. Journal of the American Geriatrics Society 2020:68;S49–S54. PMID: 32589274 DOI: 10.1111/jgs.16617
  • Zheng Y, Jiang Y, Dorsch M, Ding Y, Vydiswaran VGV, Lester CA. Work effort, readability, and quality of outpatient pharmacy transcription of patient directions from electronic prescriptions: a retrospective observational cohort analysis. BMJ Quality & Safety. 2020. PMID: 32451350 DOI: 10.1136/bmjqs-2019-010405
  • Vydiswaran VGV, Romero DM, Zhao X, Yu D, Gomez-Lopez I, Lu JX, Iott B, Baylin A, Jansen EC, Clarke P, Berrocal VJ, Goodspeed R, Veinot T. Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics. Journal of the American Medical Informatics Association. 2020;27(2):254–64. PMID: 31633756 DOI: 10.1093/jamia/ocz181
  • Marshall E, Moon MA, Mirchandani A, Smith G, Nichols LP, Zhao X, Vydiswaran VGV, Chang T. “Baby wants tacos”: Analysis of health-related Facebook posts from young pregnant women. Maternal and Child Health Journal. 2019 Oct;23(10):1400–13. PMID: 31222598 DOI: 10.1007/s10995-019-02776-7.
  • Vydiswaran VGV, Strayhorn A, Zhao X, Robinson P, Agarwal M, Bagazinski E, Essiet M, Iott BE, Joo H, Ko P, Lee D, Lu JX, Liu J, Murali A, Sasagawa K, Wang T, Yuan N. Hybrid bag of approaches to characterize selection criteria for cohort identification. Journal of the American Medical Informatics Association. 2019:26(11);1172–80. PMID: 31197354. DOI: 10.1093/jamia/ocz079
  • Vydiswaran VGV, Zhang Y, Wang Y, Xu H. Special issue of BMC medical informatics and decision making on health natural language processing. BMC Medical Informatics and Decision Making, 2019:19(Suppl 3):76. DOI: 10.1186/s12911-019-0777-0 PMID: 30943961 PMCID: PMC6448180
  • Hanauer DA, Mei Q, Vydiswaran VGV, Singh K, Landis-Lewis Z, Weng C. Complexities, variations, and errors of numbering within clinical notes: The potential impact on information extraction and cohort-identification. BMC Medical Informatics and Decision Making, 2019:19(Suppl 3):75. DOI: 10.1186/s12911-019-0784-1 PMID: 30944012 PMCID: PMC6448181
  • Vydiswaran VGV, Reddy M. Identifying peer experts in online health forums. BMC Medical Informatics and Decision Making. 2019:19(Suppl 3):68. PMID: 30943973 PMCID: PMC6448182 DOI: 10.1186/s12911-019-0782-3
  • Lester CA, Wang M, Vydiswaran VGV. The patient experience described in Yelp! reviews of retail pharmacies. Journal of the American Pharmacists Association, 2019 May–June; 59(3):349–55. PMID: 31000435 DOI: 10.1016/j.japh.2019.02.004
  • DeJonckheere M, Nichols L, Vydiswaran VGV, Zhao X, Collins- Thompson K, Resnicow K, Chang T. Using text messaging, social media, and interviews to understand what pregnant youth think about weight gain during pregnancy. Journal of Medical Internet Research (JMIR) Formative Research. 2019:3(2):e11397. PMID: 30932869 PMCID: PMC6462892 DOI: 10.2196/11397.
  • Oram D, Tzilos Wernette G, Nichols LP, Vydiswaran VGV, Zhao X, Chang T. Substance use among young mothers: An analysis of Facebook posts. Journal of Medical Internet Research (JMIR) Pediatrics and Parenting. 2018;1(2):e10261 PMID: 31518312 PMCID: PMC6716430 DOI: 10.2196/10261.
  • Shen Y, Clarke P, Gomez-Lopez I, Hill A, Romero D, Goodspeed R, Berrocal V, Vydiswaran VGV, Veinot TC. Using social media to assess the consumer nutrition environment: Comparing Yelp reviews with a direct observation audit instrument for grocery stores, Public Health Nutrition. 2018 Nov 8:1–8. PMID: 30406742 DOI: 10.1017/S1368980018002872.
  • Goodspeed R, Yan X, Hardy J, Vydiswaran VGV, Berrocal VJ, Clarke P, Romero DM, Gomez-Lopez IN, Veinot TC. Comparing the data quality of Global Positioning System devices and mobile phones for assessing relationships between place, mobility, and health: Field study. Journal of Medical Internet Research (JMIR) mHealth and uHealth 2018 Aug;6(8):e168 PMID: 30104185 PMCID: PMC6111146 DOI: 10.2196/mhealth.9771
  • Guetterman T, Chang T, DeJonckheere M, Basu T, Scruggs E, Vydiswaran VGV. Augmenting qualitative text analysis with natural language processing: Methodological study. Journal of Medical Internet Research, 2018 Jun 29;20(6):e231. PMID: 29959110 PMCID: PMC6045788 DOI: 10.2196/jmir.9702
  • Vydiswaran VGV, Romero D, Zhao X, Yu D, Gomez-Lopez I, Lu JX, Iott B, Baylin A, Clarke P, Berrocal V, Goodspeed R, Veinot T. “Bacon bacon bacon”: Food-related tweets and sentiment in Metro Detroit. In Proceedings of the 12th International AAAI Conference on Weblogs and Social Media (ICWSM), 2018. pp. 692–5.
  • Hardy JK, Veinot TC, Yan X, Berrocal VJ, Clarke P, Goodspeed R, Gomez-Lopez IN, Romero DN, Vydiswaran VGV. User acceptance of location-tracking technologies in health research: Implications for study design and data quality. Journal of Biomedical Informatics. 2018 Mar;79:7–19. DOI: 10.1016/j.jbi.2018.01.003. PMID: 29355784. https://www.sciencedirect.com/science/article/pii/S1532046418300054
  • DeJonckheere M, Nichols LP, Moniz MH, Sonneville KR, Vydiswaran VGV, Zhao X, Guetterman TC, Chang T. MyVoice national text message survey of youth aged 14 to 24 years: Study protocol. Journal of Medical Internet Research (JMIR) Research Protocols. 2017 Dec; 6(12):e247. DOI: 10.2196/resprot.8502 PMID:29229587 PMCID:PMC5742661.
  • Lahiri S, Vydiswaran VGV, Mihalcea R. Identifying usage expression sentences in consumer product reviews. In the Proceedings on the Eighth International Joint Conference on Natural Language Processing (IJCNLP), Volume 1: Long papers, 2017:393–403.
  • Kinsora A, Barron K, Mei Q, Vydiswaran VGV. Creating a Labeled Dataset for Medical Misinformation in Health Forums. In Proceedings of the 2017 IEEE International Conference on Healthcare Informatics (ICHI). 2017:456–61.
  • Gomez-Lopez IN, Clarke P, Hill AB, Romero DM, Goodspeed R, Berrocal VJ, Vydiswaran VGV, Veinot TC. Using social media to identify sources of healthy food in urban neighborhoods. Journal of Urban Health. 2017 Jun;94(3):429–36. doi: 10.1007/s11524-017-0154-1. PMID: 28455606 PMCID: PMC5481219.
  • Hanauer DA, Wu DTY, Yang L, Mei Q, Steffy KM, Vydiswaran VGV, Zheng K. Development and empirical evaluation of semantically-based query recommendation for an electronic health record search engine. Journal of the Biomedical Informatics (JBI). 2017 Mar;67:1–10. DOI: 10.1016/j.jbi.2017.01.013. PMID: 28131722 PMCID: PMC5378386.
  • Huang J, Xu K, Vydiswaran VGV. Analyzing multiple medical corpora using word embedding. In Proceedings of the 2016 IEEE International Conference on Healthcare Informatics (ICHI). 2016:527–33. DOI: 10.1109/ICHI.2016.94.
  • Subrahmanian VS, Azaria A, Durst S, Kagan V, Galstyan A, Lerman K, Zhu L, Ferrara E, Flammini A, Menczer F, Waltzman R, Stevens A, Dekhtyar A, Gao S, Hogg T, Kooti F, Liu Y, Varol O, Shiralkar P, Vydiswaran VGV, Mei Q, Huang T. The DARPA Twitter bot challenge. IEEE Computer. 2016 Jun;49(6):38–46. Also arXiv:1601.05140 [cs.SI]
  • Pal J, Chandra P, Vydiswaran VGV. Twitter and the rebranding of Narendra Modi. Economic and Political Weekly. 2016 Feb:51(8);52–60.
  • Wu DTY, Hanauer DA, Mei Q, Clark PM, An LC, Proulx J, Zeng QT, Vydiswaran VGV, Collins-Thompson K, Zheng K. Assessing the readability of ClinicalTrials.gov. Journal of the American Medical Informatics Association (JAMIA). 2016 Mar;23(2):269–75. DOI: 10.1093/jamia/ocv062. Epub 2015 Aug 11. PMID: 26269536. PMCID: PMC5009924.
  • Zheng K, Vydiswaran VGV, Liu Y, Wang Y, Stubbs A, Uzuner Ö, Gururaj AE, Bayer S, Aberdeen J, Rumshisky A, Pakhomov S, Liu H, Xu H. Ease of adoption of clinical natural language processing software: An evaluation of five systems. Journal of Biomedical Informatics (JBI) Special Issue on Proceedings of the 2014 i2b2/UTHealth Shared Tasks and Workshop on Challenges in Natural Language Processing for Clinical Data. Uzuner Ö and Stubbs A (eds.) 2015 Dec: 58 Suppl; S189–96. DOI: 10.1016/j.jbi.2015.07.008. PMID: 26210361. PMCID: PMC4974203.
  • Vydiswaran VGV, Zhai CX, Roth D, Pirolli P. Overcoming bias to learn about controversial topics. Journal of the American Society for Information Science and Technology (JASIST) 2015;16(8):1655–72. DOI: 10.1002/asi.23274
  • Vydiswaran VGV, Mei Q, Hanauer DA, Zheng K. Mining consumer health vocabulary from community-generated text. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA) 2014:1150–9. PMID: 25954426. PMCID: PMC4419967. Distinguished Paper Award.
  • Vydiswaran VGV, Liu Y, Zheng K, Hanauer DA, Mei Q. User-created groups in health forums: What makes them special? In Proceedings of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM) 2014:515–24.
  • Vydiswaran VGV, Zhai CX, Roth D, Pirolli P. BiasTrust: Teaching biased users about controversial topics. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM) 2012:1205–9.
  • Vydiswaran VGV, Zhai CX, Roth D, Pirolli P. Unbiased learning of controversial topics. In Proceedings of the 75th Annual Meeting of the American Society for Information Science and Technology (ASIS&T) 2012:291.1–4.
  • Sondhi P, Vydiswaran VGV, Zhai CX. Reliability prediction of webpages in the medical domain. In Proceedings of the 34th European Conference on Information Retrieval (ECIR) 2012:219–31.
  • Vydiswaran VGV, Zhai CX, Roth D. Content-driven trust propagation framework. In Proceedings of the 17th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2011:974–82.
  • Vydiswaran VGV, van den Eijkhof J, Chandrasekar R, Paradiso A, St. George J. News Sync: Enabling scenario-based news exploration. In Proceedings of the 74th Annual Meeting of the American Society for Information Science and Technology (ASIS&T) 2011:78.1–10.
  • Sammons M, Vydiswaran VGV, Roth D. “Ask not what textual entailment can do for you …”. In Proceedings of the 48th Annual Meeting of the Association of Computational Linguistics (ACL) 2010:1199–208.
  • Roth D, Sammons M, Vydiswaran VGV. A framework for entailed relation recognition. In Proceedings of the 47th Annual Meeting of the Association of Computational Linguistics (ACL) 2009:57–60.
  • Vydiswaran VGV, Sarawagi S. Learning to extract information from large websites using sequential models. In Proceedings of the 11th International Conference on Management of Data (COMAD) 2005:3–14. Best Paper Award.

Peer-Reviewed Workshop Publications

  • Simancek D, Vydiswaran VGV. Handling name errors of a BERT-based de-Identification system: Insights from stratified sampling and Markov-based pseudonymization. In Proceedings of the Computational Approaches to Language Data Pseudonymization (CALD-Pseudo) workshop at EACL 2024. In print.
  • Chang CY, Li J, Kumar S, Vydiswaran VGV. StellEllaStars at MedIQA-Sum 2023: Exploring transformer-based models for Dialogue2Topic classification. In the CEUR-WS Proceedings 2023.
  • Li Q, Ren X, Vydiswaran VGV. LHS712EE at BioLaySumm 2023: Using BART and LED to summarize biomedical research articles. In Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and Shared Tasks (BioNLP) 2003, pages 620–4. https://aclanthology.org/2023.bionlp-1.66
  • Han P, Yu D, Vydiswaran VGV. Medication mention extraction in tweets using DistilBERT with bootstrapping. In Proceedings of the BioCreative VII Challenge Evaluation Workshop. 2023, pages 198–200.
  • Iott BE, Yu D, Beals A, Romero DM, Vydiswaran VGV, Veinot TC. Using geocoded social media data to assess physical activity levels of communities: A study of Twitter users from Metropolitan Detroit. In the AMIA Workshop on Interactive Systems in Healthcare (WISH), 2020.
  • Vydiswaran VGV, Yu D, Zhao X, Carr E, Martindale J, Xiao J, Ghannam N, Althoen M, Castellanos A, Patel N, Vasquez D. Identifying medication abuse and adverse effects from tweets: University of Michigan at #SMM4H 2020. In Proceedings of the Fifth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task. 2020:90–4. https://www.aclweb.org/anthology/2020.smm4h-1.13
  • Vydiswaran VGV, Ganzel G, Romas B, Yu D, Austin AM, Bhomia N, Chan S, Hall SV, Le V, Miller A, Oduyebo O, Song A, Sondhi R, Teng D, Tseng H, Vuong K, Zimmerman S. Towards text processing pipelines to identify adverse drug events-related tweets: University of Michigan @ SMM4H19 Task 1. In Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task. 2019:107–9.
  • Zhao X, Yu D, Vydiswaran VGV. Identifying adverse drug events mentions in tweets using attentive, collocated, and aggregated medical representation. In Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task. 2019:62–70.
  • Hanauer DA, Mei Q, Vydiswaran VGV, Singh K, Landis-Lewis Z, Weng C.  Numerical age variations within clinical notes: The potential impact on de-identification and information extraction. In Proceedings of the IEEE International Conference on Healthcare Informatics Workshop (ICHI-W), 2018:66–7.
  • Reddy M, Vydiswaran VGV. Towards identifying peer expertise in online health forums. In Proceedings of the IEEE International Conference on Healthcare Informatics Workshop (ICHI-W), 2018:82–3.
  • Vydiswaran VGV, Zhai CX, Roth D. Gauging the Internet doctor: Ranking medical claims based on community knowledge. In Proceedings of the KDD Workshop on Data Mining for Medicine and HealthCare 2011:42–51. doi: 10.1145/2023582.2023589
  • Vydiswaran VGV, van den Eijkhof J, Chandrasekar R, Paradiso A, St. George J. News Sync: Three reasons to visualize news better. In Proceedings of the Fourth Workshop on Human-Computer Interaction and Information Retrieval (HCIR) 2010 August 22:45–8.
  • Vydiswaran VGV, Chandrasekar R. Improving the online news experience. In Proceedings of the Fourth Workshop on Human-Computer Interaction and Information Retrieval (HCIR) 2010 August 22:122–5.

Peer-reviewed Abstracts

  • Alkiek K, Simancek D, Tan J, Weissman N, Ferraro J, Vydiswaran VGV. DeiDoc: Automatic de-identification of notes using long-document transformers. In Annual Symposium of the American Medical Informatics Association. 2023.
  • Wu W, Najarian C, Vydiswaran VGV, Bynum J, Mahmoudi E. Leveraging natural language processing to identify social determinants of health for patients with Alzheimer’s disease and related dementias from electronic medical records. Alzheimer’s Dement. 2023;19(Suppl 5):e061634. https://doi.org/10.1002/alz.061634
  • Dorr DA, Weiskopf N, Bobo M, Dunne MJ, Han P, Kim J, Vydiswaran VGV. Validating complex phenotypes: A structured approach for dementia. AMIA 2022.
  • Zhao X, Yu D, Bishu S, Rice MD, Vydiswaran VGV, Stidham R. Automated reporting of medication use history for inflammatory bowel disease using natural language processing of clinical notes us accurate and outperforms electronic administrative records. Digestive Disease Week (DDW) 2022. Accepted as an Oral presentation.
  • Pandian B, Lakshmanan SS, Vandervest JC, Mentz G, Kheterpal S, Vydiswaran VGV, Burns ML. Generalizing machine learning models from medical free text. Under review at AUA IARS 2022.
  • Bragg-Gresham JL, Gillespie BW, Singh K, Zhang X, Han Y, Steffick D, Shahinian V, Weitzel W, Vydiswaran VGV, Veinot TC, Crowley ST, Saran R. Developing a prediction model for incidence of newly detected chronic kidney disease (CKD) among US veterans, 2009-2018. American Society of Nephrology Kidney Week, 2021.
  • Han Y, Bragg-Gresham JL, Steffick D, Zhang X, Wyncott A, Veinot TC, Vydiswaran VGV, Gillespie BW, Weitzel W, Singh K, Crowley ST, Saran R. Social determinants of health (SDOH), environmental inequities, and end-stage renal disease (ESRD) among US veterans: An integration of ecological and spatial approaches. American Society of Nephrology Kidney Week, 2021.
  • Vydiswaran VGV, Strayhorn A, Stevens H, Fernandez A. Leveraging electronic health records to identify high-risk alcohol use prior to surgery. RSA/ISBRA-2021. Alcoholism: Clinical and Experimental Research, June supplement.
  • Bragg-Gresham J, Gillespie B, Zhang X, Han Y, Steffick D, Wyncott A, Veinot T, Vydiswaran VGV, Weitzel W, Singh K, Crowley S, Saran R. Time trends and spatial distribution of newly detected chronic kidney disease among US veterans, 2009-2018. American Society of Nephrology Kidney Week, 2020.
  • Han Y, Bragg-Gresham JL, Steffick D, Zhang X, Wyncott A, Veinot TC, Vydiswaran VGV, Gillespie BW, Weitzel W, Singh K, Crowley ST, Saran R. Incidence of CKD and environmental inequities: an integration of ecological and spatial approach in US veterans. American Society of Nephrology Kidney Week, 2020.
  • Stidham R, Yu D, Lahiri S, Vydiswaran VGV. Detection and characterization of extra-intestinal manifestations of IBD in clinical office notes using natural language processing. Gastroenterology, 2020 May;158(6):S-702. DOI: 10.1016/S0016-5085(20)32446-X
  • Stidham R, Yu D, Lahiri S, Vydiswaran VGV. Detection and characterisation of extra-intestinal manifestations of IBD in clinical office notes using natural language processing. Journal of Crohn’s and Colitis. 2020 Jan;14(Supplement_1): S309–S310. DOI: 10.1093/ecco-jcc/jjz203.440
  • Joo H, Hu Y, Mathis MR, Vydiswaran VGV. Early prediction of heart failure using attention models from clinical notes. In Proceedings of the American Medical Informatics Association Informatics Summit, 2019, page 881–882. Podium Abstract.
  • Jiang Y, Vydiswaran VGV, Lee YE, Joo H, Zheng A, Harris MR. Feasibility of identifying oral anticancer agent toxicity self-reporting and management advice from clinical notes. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2018, page 2010.
  • Lee AJ, Fu S, Vydiswaran VGV. Supervised learning approach to link prediction in FDA Adverse Event Reporting System (FAERS) database network. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2018, page 1748–1749. Podium Abstract.
  • Vydiswaran VGV, Cole M, Zheng A, Mahajan P. Can machine learning assess students’ clinical reasoning? Using natural language processing to grade medical students’ written assessment and plan. In the annual Association for Medical Education in Europe (AMEE) Conference, 2018.
  • Guetterman T, DeJonckheere M, Chang T, Basu T, Scrubs E, Vydiswaran VGV. Integrating Natural Language Processing with Qualitative Text Analysis in Mixed Methods Studies with a Large Qualitative Strand. In the third Mixed Methods International Research Association (MMIRA) International Conference, 2018.
  • Cole M, Vydiswaran VGV, Zheng A, Mahajan P. A novel method to train natural language processing to evaluate medical decision making using medical student assessments. In the Annual meeting of the Society for Academic Emergency Medicine (SAEM), 2018. Highlighted as a fantastic poster in the “SAEM Professor Rounds” (https://www.saem.org/annual-meeting/education/saem-professor-rounds)
  • Marshall E, Moon MA, Smith G, Mirchandani A, Zhao X, Vydiswaran VGV, Chang T. “Baby wants tacos”: Analysis of health-related Facebook posts from young pregnant women. In the Annual 2018 Fellows, Residents, Or Students Research Works-in-Progress Poster. 2018 Annual Spring Conference, Society of Teachers of Family Medicine.
  • Mahajan P, Alpern E, Baird-Cox K, Boothman R, Chamberlain J, Cosby K, Duffy E, Epstein H, Gegenheimer-Holmes J, Gerardi M, Giardina T, Mathias E, Mollen C, Patel V, Radecki R, Ruddy R, Saleem J, Shaw K, Sittig DF, Vydiswaran VGV, Singh H. Opportunities to Improve Diagnosis in Acute Care – Findings from a Multi-Disciplinary Expert Panel. In Diagnostic Error in Medicine: 10th International Conference (Applied Innovations), 2017.
  • Chang T, Oram D, Nichols L, Tzilos-Wernette G, Vydiswaran VGV, Zhao X. Substance use among young mothers: An analysis of Facebook posts. In the North American Primary Care Research Group (NAPCRG) Annual Meeting (Research in Progress), 2017.
  • Plegue M, Nichols L, Chang T, Dejonckheere M, Czuhajewski C, Vydiswaran VGV. Hashtag health: Designing effective, timely, and trustworthy patient education campaigns in the age of information overload. In the North American Primary Care Research Group (NAPCRG) Annual Meeting, 2017.
  • Chang T, Plegue M, Nichols L, Czuhajewski C, Dejonckheere M, Vydiswaran VGV. Engaging youth in a longitudinal text message survey: implications for research and practice. In the North American Primary Care Research Group (NAPCRG) Annual Meeting, 2017. Oral presentation.
  • Wang Y, Tang J, Vydiswaran VGV, Zheng K, Xu H, Mei Q. Matching consumer health vocabulary with professional medical terms through concept embedding. In Proceedings of  the American Medical Informatics Association Annual Symposium (AMIA), 2017, page 2218.
  • Zhao X, Vydiswaran VGV. HyDeXT: A hybrid de-identification and extraction tool for health text. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2017, page 2250.
  • Reynolds TL, Vydiswaran VGV, Wu Y, Mei Q, Hanauer DA, Zheng K. Identifying patterns indicative of copying/pasting behavior in patient generated online content. In Proceedings of the American Medical Informatics Association Annual Symposium (AMIA), 2015, page 1654.
  • Zheng K, Hanauer DA, Mei Q, Vydiswaran VGV, Wu DTY. Bridging the gap between information availability and information. In Proceedings of the 25th Annual Pediatric Research Symposium, Department of Pediatrics and Communicable Diseases, University of Michigan Medical School, 2014.
  • Vydiswaran VGV, Liu Y, Zheng K, Hanauer DA, Mei Q. Study of user-created groups in health forums. In Proceedings of the 25th Annual Pediatric Research Symposium, Department of Pediatrics and Communicable Diseases, University of Michigan Medical School, 2014.

Non Peer-Reviewed Publications

  • Liu J, Kronk C, Su WC, Wu DTY, Vydiswaran VGV. Retrieving scientific abstracts: MedIER at TREC 2018 Precision Medicine Track. In Ellen M. Voorhees and Angela Ellis, editors, National Institute of Standards and Technology (NIST) Special Publication 500-331: The Twenty-Seventh Text REtrieval Conference Proceedings (TREC 2018). 2018:1–6.
  • Yin T, Wu DTY, Vydiswaran VGV. Retrieving documents based on gene name variations: MedIER at TREC 2017 Precision Medicine Track. In Ellen M. Voorhees and Angela Ellis, editors, National Institute of Standards and Technology (NIST) Special Publication 500-324: The Twenty-Sixth Text REtrieval Conference Proceedings (TREC 2017). 2017:1–5.
  • Hu F, Wu DTY, Mei Q, Vydiswaran VGV. Learning from medical summaries: The University of Michigan at TREC 2015 Clinical Decision Support Track. In Ellen M. Voorhees and Angela Ellis, editors, National Institute of Standards and Technology (NIST) Special Publication 500-319: The Twenty-Fourth Text REtrieval Conference Proceedings (TREC 2015). 2015:1–7.
  • Do Q, Roth D, Sammons M, Tu Y, Vydiswaran VGV. Robust, light-weight approaches to compute lexical similarity. In Computer Science Research and Technical Reports, University of Illinois 2009:1–6. Technical report: http://cogcomp.cs.illinois.edu/papers/DRSTV09.pdf
  • Lv Y, He J, Vydiswaran VGV, Ganesan K, Zhai CX. A study of term proximity and document weighting normalization in pseudo relevance feedback – UIUC at TREC 2009 Million Query Track. In Ellen M. Voorhees and Lori P. Buckland, editors, Proceedings of the 18th Text REtrieval Conference (TREC). Special Publication 500-278. National Institute of Standards and Technology (NIST) 2009:1–5.
  • Vydiswaran VGV, Ganesan K, Lv Y, He J, Zhai CX. Finding related entities by retrieving relations: UIUC at TREC 2009 Entity Track. In Ellen M. Voorhees and Lori P. Buckland, editors, Proceedings of the 18th Text REtrieval Conference (TREC). Special Publication 500-278. National Institute of Standards and Technology (NIST) 2009:1–6.
  • Sammons M, Vydiswaran VGV, Vieira T, Johri N, Chang MW, Goldwasser D, Srikumar V, Kundu G, Tu Y, Small K, Rule J, Do Q, Roth D. Relation alignment for textual entailment recognition. In Proceedings of the Text Analysis Conference (TAC), National Institute of Standards and Technology (NIST) 2009:1–10.
  • Kim HD, Park DH, Vydiswaran VGV, Zhai CX. Opinion summarization using entity features and probabilistic sentence coherence optimization: UIUC at TAC 2008 Opinion Summarization Pilot. In Proceedings of the Text Analysis Conference (TAC), National Institute of Standards and Technology (NIST) 2008:1–10.
  • Sarawagi S, Vydiswaran VGV. Learning to extract information from large domain-specific websites using sequential models. In the Special issue of ACM SIGKDD Explorations on Web content mining 2004 Dec;6(2):61–6.
  • Sarawagi S, Srinivasan S, Vydiswaran VGV, Bhudhia K. Resolving citations in a paper repository. In ACM SIGKDD Explorations 2003 Dec;5(2):91–2.

Book Chapters

  • Sammons M, Vydiswaran VGV, Roth D. Recognizing Textual Entailment. In Daniel M. Bikel and Imed Zitouni, editors, Multilingual Natural Language Processing Applications: From Theory to Practice. Prentice Hall. 2012:209–58.

Tutorial Abstracts

  • Vydiswaran VGV, Zhao X, Yu D. Data Science and natural language processing to extract information in clinical domain. CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), 2022 Jan: pages 352–3. DOI:10.1145/3493700.3493773
  • Pasternack J, Roth D, Vydiswaran VGV. Information Trustworthiness. Tutorial abstract in the 27th AAAI Conference on Artificial Intelligence (AAAI), 2013.
  • Sammons M, Szpektor I, Vydiswaran VGV. Textual Entailment. In the Tutorial Abstracts of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) 2010:21–4.

Other Abstracts

  • Yu D, Vydiswaran VGV. Natural language processing approaches to detect mentions of drugs and adverse drug events in tweets. #UMTweetCon2019 conference, University of Michigan 2019.
  • Wu Y, Vydiswaran VGV. Analyzing medical information on online social media. In Proceedings of the 2015 Undergraduate Research Opportunity Program (UROP) Spring Research Symposium, University of Michigan 2015.
  • Reddy M, Vydiswaran VGV, Mei Q. Peer experts in online health forums. In the second Machine Learning and Data Analytics Symposium (MLDAS), Qatar Computing Research Institute. Doha, Qatar 2015 Mar.
  • Iott BE, Veinot TC, Romero DM, Zhao X, Lu JX, Yu D, Gomez-Lopez I, Vydiswaran VGV. Construction of a food-specific sentiment keyword dictionary for machine classification of tweets. In the Annual Meeting of the American Medical Informatics Association (AMIA) 2017 pre-symposium workshop of the Natural Language Processing Working Group.
  • Agarwal A, Vydiswaran VGV. Identifying medical rumor frequency and credibility of provided supporting evidence. In Proceedings of the 2016 Undergraduate Research Opportunity Program (UROP) Spring Research Symposium, University of Michigan 2016.
  • Do Q, Vydiswaran VGV, Roth D. New search paradigms for meaning-based information retrieval. In the Second Annual University Network Summit of the Department of Homeland Security, Washington D.C., November 2008.

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