Publications

A complete list of publications is available from Mike Conway's Google Scholar page.

2024

• Similarity ranking of case law using propositions as features. Curran, Conway.  Proceedings of the 16th Japanese Society for Artificial Intelligence International Symposia (JSAI-isAI). (2024)
• A theory-informed deep learning approach to extracting and characterizing substance use-related stigma in social media.  Roesler, Johnny, Conway, Chen.  BMC Digital Health. 2, 1 (2024)
• Generating mental health transcripts with SAPE (Spanish Adaptive Prompt Engineering).  Lozoya, Berazaluce, Perches, Lúa, Conway, D’Alfonso.  NAACL (2024)
  
• Intervention extraction in preclinical animal studies of Alzheimer's Disease:  enhancing regex performance using language model-based filtering.  Pu, Hair, Beck, Conway, MacLeod, Verspoor.  BioNLP (2024)
• Optimizing multimodal large language models for detection of alcohol advertisements via adaptive prompting.  Lozoya, Liu, D'Alfonso, Conway.  BioNLP (2024)
  
• The use of NLP methods in Reddit to investigate opioid use:  scoping review.  Almeida, Patton, Conway, Gupta, Strathdee, Borquez.  JMIR Infodemiology 4, e51156 (2024)
• MLBMIKABR at “Discharge Me!”: Concept Based Clinical Text Description Generation.  Naskar, Hocking, Chondros, Boyle, Conway. BioNLP (2024)
• Development of a natural language processing system to identify clinical documentation of electronic cigarette use.  Alba, Gan, Hu, Zhu, Duvall, Conway.   Studies in Health Technology and Informatics. 310:659-663 (2024)
  
• Automatic extraction of skin and soft tissue infection status from clinical notes. Rhoads, Christensen, Westerdahl, Stevens, Chapman, Conway. Studies in Health Technology and Informatics.  10:579-583 (2024)

2023

• Evaluation of the Boys Do Cry suicide prevention media campaigns on Twitter. Scottie Requena, Pirkis, Currier, Conway, Le, Turnure, Cummins, Nicholas. JMIR Formative Research.  7 (2023)
• Identifying gender bias in generative models for mental health synthetic data. Cabrera-Lozoya, D'Alfonso, Conway.  2023 IEEE 11th International Conference on Healthcare Informatics (ICHI) - Sixth International Workshop on Health Natural Language Processing (Health NLP) (2023)
• WhatsApp group discussion for smoking relapse prevention:  a randomized control trial (abridged secondary publication).  Cheung, Chan, Conway, Wong, Li, Wang, Lam. Hong Kong Medical Journal.  29, 3 (2023)
  
• Natural language processing for clinical text. Rozova, Liu, Conway.  Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association (ALTA) (2023) [Tutorial paper - not peer reviewed]
  
• Using social media data to investigate public perceptions of cannabis as a medicine: narrative review. Khademi, Hallinan, Conway, Bonomo. Journal of Medical Internet Research. 25 (2023)
• Leveraging natural language processing to extract features of colorectal polyps from pathology reports for retrospective study.  Benson, Winterton, Winn, Krick, Liu, Abu-el Rub, Conway, Del Fiol, Gawron, Hardikar.  JCO Clinical Cancer Informatics.  JCO Clinical Cancer Informatics, 7 (2023)
  

2022

• Perspectives of the COVID-19 pandemic on Reddit: Comparative natural language processing study of the United States, the United Kingdom, Canada, and Australia. Hu, Conway. JMIR Infodemiology. 2, 2 (2022)
  
• Consumer-generated discourse on cannabis as a medicine: Scoping review of techniques. Khademi Habibabadi, Hallinan, Bonomo, Conway.  Journal of Medical Internet Research. 24, 11 (2022)
  
• Pain points in parents' interactions with newborn screening systems:  a qualitative study.  Conway, Vuong, Hart, Rorhwasser, Eilbeck.  BMC Pediatrics. 22, 167 (2022)
• Substance use-related stigma:  an exploratory study of search behavior using Google Trends (2004-2021).  Conway, Citrenbaum, Chen.  American Journal of Drug & Alcohol Abuse (2022) [data][preprint]
• Social media discourse and internet search queries on cannabis as a medicine: A systematic review.  Khademi Habibabadi, Bonomo, Conway, Hallinan. MedRxiv (2022)
  
• Examining stigma relating to substance use and contextual factors in social media discussions.  Chen, Johnny, Conway. Drug & Alcohol Dependence Reports (2022)
  
• Examining cannabis, tobacco, and vaping discourse on Reddit:  an exploratory approach using natural language processing.  Benson, Hu, Chen, Zhu, Conway.  Frontiers in Public Health (2022).
  

2021

• Vaping at the VA:  developing an annotated corpus of electronic cigarette mentions in clinical notes at the Department of Veterans Affairs.  Conway, Alba, Zhu, Patterson.  In Proceedings of the American Medical Informatics Association Symposium. (2021).
• Determining the prevalence of cannabis, tobacco, and vaping device mentions in online communities using natural language processing.  Hu, Benson, Chen, Zhu, Conway.  Drug & Alcohol Dependence (2021).
• A scoping review and content analysis of common depressive symptoms of young people.  Guo, Keeshin, Conway, Chapman, Sward. The Journal of School Nursing (2021). 
  
• Adaptation of an NLP system to a new healthcare environment to identify social determinants of health.  Chapman, Reeves, Christensen, Brown, Conway, Levis, Gobbel, Shah, Goodrich, Ricket, Minter, Bohm, Bray, Matheny. Journal of Biomedical Informatics (2021).

2020

• Investigating the attitudes of adolescents and young adults towards JUUL. Benson, Hu, Chen, Nag, Zhu, Conway. JMIR Public Health & Surveillance 6, 3 (2020), e19975.
• Predicting optimal hypertension treatment pathways using recurrent neural networks.  Ye, Zeng, Facelli, Brixner, Conway, Bray. International Journal of Medical Informatics 139 (2020), 104122.
• Effectiveness of WhatsApp online group discussion for smoking relapse prevention: protocol for a pragmatic randomized controlled trial.  Cheung, Chan, Ho, Fok, Conway, Wong, Li, Wang, Lam. Addiction (2020).

2019

• Recent advances in using natural language processing to address public health research questions.  Conway, Hu, Chapman. Yearbook of Medical Informatics (2019), pp 208–217.
• Moonstone: a novel natural language processing system for inferring social risk from clinical narratives.  Conway, Keyhani, Christensen, South, Vali, Walter, Mowery, Abdelrahman, Chapman. Journal of Biomedical Semantics 10, 1 (2019).
• The PsyTAR dataset:  from patient-generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications.  Zolnoori, Fung, Patrick, Fontelo, Kharrazi, Faiola, Wu, Elderedge, Luo, Conway, Zhu, Park, Xu, Moayyed.  Data in Brief 24 (2019).
• Documentation of ENDS use in the Veterans Affairs electronic health record.  Conway, Mowery, South, Stoddard, Chapman, Patterson, Zhu.  American Journal of Preventive Medicine 56, 3 (2019) pp 474-475.
• A systematic approach for developing a corpus of patient reported adverse drug events:  a case study for SSRI and SNRI medications.  Zolnoori, Wah, Patrick, Fontelo, Kharrazi, Faiola, Wu, Eldredge, Luo, Conway, Zhu, Kyung-Park, Xu, Moayyed, Goudarzvand.  Journal of Biomedical Informatics (2019), 103091.

2018

• Cross disciplinary consultancy to bridge public health technical needs and analytic developers: negation detection use case. Conway, Mowery, Ising, Velupillai, Doan, Gunn, Donovan, Wiedman, Ballister, Soetebier, Tong, Burkom.  Online Journal of Public Health Informatics 10, 2 (2018), e209.
• Characterizing websites that provide information about complementary and integrative health: systematic search and evaluation of five domains. Chen, Taylor-Swanson, Buie, Park, Conway.  Interactive Journal of Medical Internet Research 7, 2 (2018), e14.
• Exploring physician attitudes regarding electronic documentation of e-cigarette use: a qualitative study.  Hurst, Conway.  Tobacco Use Insights 11 (2018).
• Examining thematic similarity, difference, and membership in three online mental health communities from Reddit:  a text mining and visualization approach.  Park, Conway, Chen. Computers in Human Behavior 78 (2018) pp 98-112.
• Harnessing Reddit to understand the written-communication challenges experienced by individuals with mental health disorders:  analysis of texts from mental health communities.  Park, Conway.  Journal of Medical Internet Research 20, 1 (2018), e121.
• How do you #relax when you're #stressed?  a content analysis and infodemiology study of stress-related tweets.  Doan, Ritchart, Perry, Chaparro, Conway.  JMIR Public Health and Surveillance 3, 2 (2017).
• Applying the transtheoretical model of behavioral change to Reddit data: a pilot study of cessation strategies and outcomes among tobacco users. Mowery, Park, Conway. In UK Healthcare Text Analytics Conference (HealTAC-2018). 2018.
  

2017

• Longitudinal changes in psychological states in online health community members:  understanding the long-term effects of participating in an online depression community.  Park, Conway. Journal of Medical Internet Research 19, 3 (2017), e71.
• Understanding depressive symptoms and psychosocial stressors on Twitter:  a corpus-based study.  Mowery, Coppersmith, Stoddard, Smith, Cheney, Conway.  Journal of Medical Internet Research 19, 2 (2017), e48.
• The readability of electronic cigarette health information
  and advice: a quantitative analysis of web-based information.  Park, Zhu, Conway.  JMIR Public Health & Surveillance 3, 1 (2017), e1.
• Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis.  Mowery, Chapman, Conway, South, Madden, Keyhani, Chapman.  Journal of Biomedical Semantics 7 (2017), 26.
• Investigating patient attitudes towards the use of social media data to augment depression diagnosis and treatment: a qualitative study. Mikal, Hurst, Conway. In Proceedings of the Workshop on Computational Linguistics and Clinical Psychology — From Linguistic Signal to Clinical Reality (CLPsych 2017). 2017, pp. 41–47.
• A corpus analysis of social connections and social isolation for patients suffering from major depressive disorder in clinical notes. Guo, Mowery, Sward, Conway.  In Proceedings of the Workshop on Computational Linguistics and Clinical Psychology — From Linguistic Signal to Clinical Reality (CLPsych 2017). 2017, pp. 26–31.
• Investigating the documentation of electronic cigarette use in the Veteran Affairs electronic health record: a pilot study. Mowery, South, Patterson, Zhu, Conway. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, Vancouver (BioNLP 2017). 2017.
• Tracking health-related discussions on Reddit for public health
  applications.  Park, Conway.  In Proceedings of the American Medical Informatics Association Symposium. 2017, pp 1362–1371.
• Feature studies to inform the classification of depressive symptoms from  Twitter data for population health.  Mowery, Bryan, Conway.  In Proceedings of the WSDM 2017 Workshop on Mining Online Health Reports. 2017.
• Understanding patient satisfaction with received healthcare services: a natural language processing approach.  Doing-Harris, Mowery, Daniels, Chapman, Conway. In Proceedings of the American Medical Informatics Association Symposium. 2016, pp 524–533.
  

2016

• Ethical issues in using Twitter for population-level depression monitoring:  a qualitative study.  Mikal, Hurst, Conway.  BMC Medical Ethics 17, 1 (2016).
• Social media, big data, and mental health:  current advances and ethical implications.  Conway, O'Connor.  Current Opinion in Psychology 9 (2016) pp 77-82.
• Developing a web-based SKOS editor.  Conway, Khojoyan, Fana, Scuba, Tharp, Chapman, Jupp.  Journal of Biomedical Semantics 7, 5 (2016).
• Towards automatically classifying depressive symptoms from Twitter data for population health. Mowery, Park, Conway. In PEOPLES: Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media. 2016, pp 182–191.
• Vocabulary development to support information extraction of substance abuse from psychiatry notes. Velupillai, Mowery, Conway, Hurdle, Kious. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, Berlin (BioNLP 2016). 2016, pp 92–101.
• Dietary management software for chronic kidney disease: current status and open issues. Chen, Murtaugh, Koebnick, Beddhu, Garvin, Conway, Lee, Gouripeddi, Luo. In The 38th Annual International Conference of the
  IEEE Engineering in Medicine and Biology Society (EMBC’16). 2016, pp 62–72.
• From event detection to story telling on microblogs. Kalyanam, Velupillai, Conway, Lanckriet.   Proceedings of the ACM/IEEE Conference on Advances in Social Network Analysis and Mining, 2016, 437–442.
  

2015

• Cross-disciplinary consultancy to bridge public health technical needs and solution development expertise: asyndromic surveillance use case.  Faigen, Deyneka, Ising, Neill, Conway, Fairchild, Gunn, Swenson, Painter, Johnson, Kiley, Streichert, Burkom.  Online Journal of Public Health Informatics 7, 3 (2015).
• Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug effects.  Alvaro, Conway, Doan, Lofi, Overington, Collier.  Journal of Biomedical Informatics 58 (2015) pp 280-287.
• What online communities can tell us about electronic cigarettes and hookah use:  a study using text mining techniques.  Chen, Zhu, Conway.  Journal of Medical Internet Research 17, 9 (2015), e220.
• Using social media for actionable disease surveillance:  systematic literature review. Cameron, Charles-Smith, Conway, Corley, Lau, Olsen, Pavlin, Reynolds, Shigematsu, Streichert, Suda, Valkova.  PLoS One 10, 10, (2015), e0139701.
• Consumer attitudes towards hookah, cigarettes, and cigars:  applying topic modelling to Twitter data.  Jain, Zhu, Conway.  Tobacco Regulatory Science 6, 3 (2015) pp 198-203.
• Facts and fabrications about Ebola: A Twitter-based study. Kalyanam, Velupillai, Doan, Conway, Lanckriet. In BigCHat: Connected Health at Big Data Era — A KDD 2015 Workshop. 2015.
• Towards Developing an Annotation Scheme for Depressive Disorder Symptoms: A preliminary study using Twitter data. Mowery, Bryan, Conway. In Proceedings of the 2015 Workshop on Computational Linguistics and Clinical Psychology — From Linguistic Signal to Clinical Reality. 2015, pp 89–98.
  

2014

• Ethical issues in using Twitter for public health surveillance and research:  developing a taxonomy of ethical concepts from the research literature.  Conway.  Journal of Medical Internet Research  16, 12 (2014), e290.
• PhenDisco:  phenotype discovery systems for the database of genotypes and phenotypes (dbGAP).  Doan, Lin, Conway, Hsieh, Feudjio-Feupe, Garland, Ross, Jiang, Farzaneh, Walker, Alipanah, Xu, Kim. Journal of the American Medical Informatics Association 21 (2014) pp 31-36.
• Natural language processing systems in biomedicine: a unified system architecture overview. Doan, Conway, Phuong, Ohno-Machado.  vol. 1168 Methods in Molecular Biology. Springer, (2014) pp 275–294.
  
• Text mining and visualization to explore e-cigarette and hookah-related social media. Chen, Zhu, Conway. In Proceedings of the 2014 Workshop on Visual Analytics in Health Care. 2014, pp 68–69.
• Developing a web-based SKOS editor. Conway, Fana, Tharp, Scuba, Chapman, Jupp.  In Proceedings of the 6th International Symposium on Semantic Mining in Biomedicine (SMBM 2014). 2014, pp 105–108.
  

2013

• Feasibility of using clinical element models (CEM) to standardize phenotype variables in dbGAP.  Lin, Conway, Kim, Kim.  PLoS One 8, 9 (2013), e76384.
• Using Twitter to examine smoking behaviour and perceptions of emerging tobacco products. Myslin, Zhu, Chapman, Conway. Journal of Medical Internet Research 15, 8 (2013).
• Text categorization of heart, lung and blood studies in the database of Genotypes and Phenotypes (dbGaP) utilizing n-grams and metadata features. Ross, Lin, Truong, Kuman, Conway. Biomedical Informatics Insights 6, (2013) pp 35-45.
• Using chief complaints for syndromic surveillance:  a review of chief complaint classifiers in North America. Conway, Dowling, Chapman. Journal of Biomedical Informatics 46, 4 (2013) pp 734–43.
• Identifying synonymy between SNOMED clinical terms of varying length using distributional analysis of electronic health records. Henriksson, Conway, Hassel, Chapman.  In Proceedings of the American Medical Informatics Association Symposium. 2013, pp 600–609.
• Corpus-driven terminology development: populating Swedish SNOMED CT with synonyms extracted from electronic health records. Henriksson, Skeppstedt, Kvist, Duneld, Conway.  Proceedings of the Twelfth Workshop on Biomedical Natural Language Processing, Sofia (2013), pp 36–44.
• Extending the NegEx lexicon for multiple languages. Chapman, Hilert, Velupillai, Kvist, Skeppstedt, Chapman, Conway, Tharp, Mowery, Deleger. In Proceedings of the 14th World Congress on Medical and Health Informatics (MedInfo 2013). 2013, pp 677–681.
  

2012

• Demographics identification: variable extraction resource (DIVER).  Hsieh, Doan, Conway, Lin, Kim. In Proceedings of the Second IEEE Conference on Healthcare Informatics, Imaging and Systems Biology, San Diego. 2012, pp 40–49. [PDF]
  

2011

• Analyzing the heterogeneity and complexity of electronic health record orientated phenotyping algorithms. Conway, Berg, Carrell, Denny, Kho, Kullo, Linneman, Pacheco, Peissig, Rasmussen, Weston, Chute, Pathak.   In Proceedings of the American Medical Informatics Association Symposium. 2011, pp 274–283.
• Developing an application ontology for mining free text clinical reports: the extended syndromic surveillance ontology. Conway, Dowling, Chapman. In Proceedings of the Third International Workshop on Health Document Text Mining and Information Analysis, Slovenia (LOUHI 2011). 2011, pp 75–82.
  

2010

• Developing syndrome definitions based on consensus and current use.  Chapman, Dowling, Baer, Buckeridge, Cochrane, Conway, Elkin, Espino, Gunn, Hales, Hutwagner, Keller, Larson, Noe, Okhmoatovskaia, Olson, Paladini, Scholer, Sniegoski, Thompson, Lober.  Journal of the American Medical Informatics Association 17, 5 (2010) pp 595–601.
• Developing a disease outbreak event corpus.  Conway, Kawazoe, Chanlekha, Collier. Journal of Medical Internet Research 12, 3 (2010), e43.
• Mining a corpus of biographical text using keywords.  Conway.  Literary & Linguistic Computing 25, 1 (2010) pp 23-35. [PDF]
  
• Leveraging the semantic web and natural language processing to enhance drug mechanism knowledge in drug product labels.  Boyce, Harkema, Conway. In Proceedings of the 2010 ACM International Health Informatics Symposium, Arlington, VA. 2010, pp 492–496.
• Developing a biosurveillance application ontology for influenza-like-illness. Conway, Dowling, Chapman.  In Proceedings of the 6th Workshop on Ontologies and Lexical Resources, Beijing. 2010, pp 58–66.
• An ontology-driven system for detecting global health events.  Collier, Matsuda-Goodwin, McCrae, Doan, Kawazoe, Conway, Kawtrakul, Takeuchi, Dien. In Proceedings of the 23rd International Conference on Computational
  Linguistics, Beijing (COLING 2010). 2010, pp 215–222.
  

2009

• Classifying disease outbreak reports using n-grams and semantic features. Conway, Doan, Kawazoe, Collier.   International Journal of Medical Informatics 78, 12 (2009) pp 47–58. [PDF]
  
• Towards role-based filtering of disease outbreak reports.  Doan, Kawazoe, Conway, Collier.  Journal of Biomedical Informatics 42, 5 (2009) pp 773–780.
• Navigating the information storm: web-based global health surveillance in BioCaster. Collier, Doan, Matsuda-Goodwin, McCray, Conway, Shigematsu, Kawazoe.  In Biosurveillance: A Health Protection Priority, T. Kass-Hout and
  X. Zhang, Eds. CRC (2009) ch. 15, pp 291–312.
• An empirical study of sections in classifying disease outbreak reports. Doan, Conway, Collier.  In Web-based Applications in Health Care and Biomedicine, A. Lazakidou, Ed., vol. 7 of Annals of Information Systems. Springer (2009) pp 47–58.
• Using hedges to enhance a disease outbreak report text mining system. Conway, Doan, Collier. In Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing, Boulder (BioNLP 2009). 2009, pp 142–143.
• Classifying disease outbreak reports using n-grams and semantic features. Conway, Doan, Kawazoe, Collier. In Proceedings of the Third International Symposium on Semantic Mining in Biomedicine (SMBM 2008), Turku, Finland. 2008, pp 29–36.
  

2008

• BioCaster: detecting public health rumors with a web-based text mining
  system.  Collier, Doan, Kawazoe, Matsuda-Goodwin, Conway, Tateno, Ngo, DIen, Kawtrakul, Takeuchi, Shigematsu, Taniguichi.   Bioinformatics 24, 24 (2008) pp 2940–2941.