Published on in Vol 15, No 11 (2013): November

Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online

Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online

Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online

Journals

  1. Xu J, Huang F, Zhang X, Wang S, Li C, Li Z, He Y. Sentiment analysis of social images via hierarchical deep fusion of content and links. Applied Soft Computing 2019;80:387 View
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  7. Sanders C, Nahar P, Small N, Hodgson D, Ong B, Dehghan A, Sharp C, Dixon W, Lewis S, Kontopantelis E, Daker-White G, Bower P, Davies L, Kayesh H, Spencer R, McAvoy A, Boaden R, Lovell K, Ainsworth J, Nowakowska M, Shepherd A, Cahoon P, Hopkins R, Allen D, Lewis A, Nenadic G. Digital methods to enhance the usefulness of patient experience data in services for long-term conditions: the DEPEND mixed-methods study. Health Services and Delivery Research 2020;8(28):1 View
  8. McLennan S. The Content and Nature of Narrative Comments on Swiss Physician Rating Websites: Analysis of 849 Comments. Journal of Medical Internet Research 2019;21(9):e14336 View
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  11. Mazzocut M, Truccolo I, Antonini M, Rinaldi F, Omero P, Ferrarin E, De Paoli P, Tasso C. Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis. Journal of Medical Internet Research 2016;18(6):e120 View
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  17. Patel S, Cain R, Neailey K, Hooberman L. General Practitioners’ Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England. Journal of Medical Internet Research 2015;17(12):e276 View
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  19. Hao H, Zhang K. The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews. Journal of Medical Internet Research 2016;18(5):e108 View
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  26. Leung R. Increasing the Impact of JMIR Journals in the Attention Economy. Journal of Medical Internet Research 2019;21(10):e16172 View
  27. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
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  29. Hart K, Perlis R, McCoy T. What do patients learn about psychotropic medications on the web? A natural language processing study. Journal of Affective Disorders 2020;260:366 View
  30. Rafferty M, Grey K. Beyond Patient Experience Surveys: Leveraging Social Media to Glean Patient Feedback. Nurse Leader 2014;12(3):31 View
  31. McCoy T, Castro V, Cagan A, Roberson A, Kohane I, Perlis R, Ramagopalan S. Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study. PLOS ONE 2015;10(8):e0136341 View
  32. Hong Y, Liang C, Radcliff T, Wigfall L, Street R. What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews. Journal of Medical Internet Research 2019;21(4):e12521 View
  33. Kim S, Oh J. Information science techniques for investigating research areas: a case study in telecommunications policy. The Journal of Supercomputing 2018;74(12):6691 View
  34. Piryani R, Madhavi D, Singh V. Analytical mapping of opinion mining and sentiment analysis research during 2000–2015. Information Processing & Management 2017;53(1):122 View
  35. Hu G, Han X, Zhou H, Liu Y. Public Perception on Healthcare Services: Evidence from Social Media Platforms in China. International Journal of Environmental Research and Public Health 2019;16(7):1273 View
  36. Czyżewski A, Hoffmann P, Szczuko P, Kurowski A, Lech M, Szczodrak M. Analysis of results of large‐scale multimodal biometric identity verification experiment. IET Biometrics 2019;8(1):92 View
  37. Emmert M, Meszmer N, Schlesinger M. A cross-sectional study assessing the association between online ratings and clinical quality of care measures for US hospitals: results from an observational study. BMC Health Services Research 2018;18(1) View
  38. Ozan-Rafferty M, Johnson J, Shah G, Kursun A. In the Words of the Medical Tourist: An Analysis of Internet Narratives by Health Travelers to Turkey. Journal of Medical Internet Research 2014;16(2):e43 View
  39. Rastegar-Mojarad M, Ye Z, Wall D, Murali N, Lin S. Collecting and Analyzing Patient Experiences of Health Care From Social Media. JMIR Research Protocols 2015;4(3):e78 View
  40. Matthies B, Coners A. Document Selection for Knowledge Discovery in Texts: Framework Development and Demonstration. Journal of Information & Knowledge Management 2017;16(04):1750038 View
  41. Boylan A, Williams V, Powell J. Online patient feedback: a scoping review and stakeholder consultation to guide health policy. Journal of Health Services Research & Policy 2020;25(2):122 View
  42. Zaman N, Goldberg D, Abrahams A, Essig R. Facebook Hospital Reviews: Automated Service Quality Detection and Relationships with Patient Satisfaction. Decision Sciences 2021;52(6):1403 View
  43. Abraham T, Deen T, Hamilton M, True G, O’Neil M, Blanchard J, Uddo M. Analyzing free-text survey responses: An accessible strategy for developing patient-centered programs and program evaluation. Evaluation and Program Planning 2020;78:101733 View
  44. Greaves F, Millett C, Nuki P. England’s Experience Incorporating “Anecdotal” Reports From Consumers into Their National Reporting System. Medical Care Research and Review 2014;71(5_suppl):65S View
  45. Wang X, Parameswaran S, Bagul D, Kishore R. Can online social support be detrimental in stigmatized chronic diseases? A quadratic model of the effects of informational and emotional support on self-care behavior of HIV patients. Journal of the American Medical Informatics Association 2018;25(8):931 View
  46. Chen D, Zhang R, Feng J, Liu K. Fulfilling information needs of patients in online health communities. Health Information & Libraries Journal 2020;37(1):48 View
  47. Gohil S, Vuik S, Darzi A. Sentiment Analysis of Health Care Tweets: Review of the Methods Used. JMIR Public Health and Surveillance 2018;4(2):e43 View
  48. Alemi F. Foreward to special issue on health analytics. Health Care Management Science 2015;18(1):1 View
  49. Urquhart C, Tbaishat D. Reflections on the value and impact of library and information services. Performance Measurement and Metrics 2016;17(1):29 View
  50. Tang C, Zhou L, Plasek J, Rozenblum R, Bates D. Comment Topic Evolution on a Cancer Institution’s Facebook Page. Applied Clinical Informatics 2017;08(03):854 View
  51. Islam M, Hasan M, Wang X, Germack H, Noor-E-Alam M. A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining. Healthcare 2018;6(2):54 View
  52. Hartley B, Elowitz E. Future Directions in Communication in Neurosurgery. World Neurosurgery 2020;133:474 View
  53. Huang M, ElTayeby O, Zolnoori M, Yao L. Public Opinions Toward Diseases: Infodemiological Study on News Media Data. Journal of Medical Internet Research 2018;20(5):e10047 View
  54. Mondal A, Cambria E, Das D, Hussain A, Bandyopadhyay S. Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis. Cognitive Computation 2018;10(4):670 View
  55. Verhoef L, Van de Belt T, Engelen L, Schoonhoven L, Kool R. Social Media and Rating Sites as Tools to Understanding Quality of Care: A Scoping Review. Journal of Medical Internet Research 2014;16(2):e56 View
  56. Patel S, Cain R, Neailey K, Hooberman L. Exploring Patients’ Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study. Journal of Medical Internet Research 2016;18(8):e217 View
  57. Jurdi Z, Crosby J, Harris J, Harvey J. A Closer Examination of the Patient Experience in the Ambulatory Space. Journal of Ambulatory Care Management 2020;43(1):89 View
  58. Xu Z, Guo H. Using Text Mining to Compare Online Pro- and Anti-Vaccine Headlines: Word Usage, Sentiments, and Online Popularity. Communication Studies 2018;69(1):103 View
  59. Zhang W, Deng Z, Hong Z, Evans R, Ma J, Zhang H. Unhappy Patients Are Not Alike: Content Analysis of the Negative Comments from China's Good Doctor Website. Journal of Medical Internet Research 2018;20(1):e35 View
  60. Liu J, Hou S, Evans R, Xia C, Xia W, Ma J. What Do Patients Complain About Online: A Systematic Review and Taxonomy Framework Based on Patient Centeredness. Journal of Medical Internet Research 2019;21(8):e14634 View
  61. Sidey-Gibbons J, Sidey-Gibbons C. Machine learning in medicine: a practical introduction. BMC Medical Research Methodology 2019;19(1) View
  62. Maramba I, Davey A, Elliott M, Roberts M, Roland M, Brown F, Burt J, Boiko O, Campbell J. Web-Based Textual Analysis of Free-Text Patient Experience Comments From a Survey in Primary Care. JMIR Medical Informatics 2015;3(2):e20 View
  63. Gibbons C, Richards S, Valderas J, Campbell J. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy. Journal of Medical Internet Research 2017;19(3):e65 View
  64. Liu N, Kauffman R. Enhancing healthcare professional and caregiving staff informedness with data analytics for chronic disease management. Information & Management 2021;58(2):103315 View
  65. Wallace B, Paul M, Sarkar U, Trikalinos T, Dredze M. A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews. Journal of the American Medical Informatics Association 2014;21(6):1098 View
  66. Shah A, Yan X, Khan S, Khurrum W, Khan Q. A multi-modal approach to predict the strength of doctor–patient relationships. Multimedia Tools and Applications 2021;80(15):23207 View
  67. Lu Y, Wu Y, Liu J, Li J, Zhang P. Understanding Health Care Social Media Use From Different Stakeholder Perspectives: A Content Analysis of an Online Health Community. Journal of Medical Internet Research 2017;19(4):e109 View
  68. KESKİN Ö, AYTEKİN Y. The Evaluation of Financial Participation Banking System in Turkey in the context of Sentiment Analysis. International Journal of Islamic Economics and Finance Studies 2019 View
  69. Li M, Xiang Y, Zhang B, Huang Z. A Sentiment Delivering Estimate Scheme Based on Trust Chain in Mobile Social Network. Mobile Information Systems 2015;2015:1 View
  70. Gebbia V, Piazza D, Valerio M, Borsellino N, Firenze A. Patients With Cancer and COVID-19: A WhatsApp Messenger-Based Survey of Patients’ Queries, Needs, Fears, and Actions Taken. JCO Global Oncology 2020;(6):722 View
  71. Greaves F, Laverty A, Cano D, Moilanen K, Pulman S, Darzi A, Millett C. Tweets about hospital quality: a mixed methods study. BMJ Quality & Safety 2014;23(10):838 View
  72. Patel S, Cain R, Neailey K, Hooberman L. Public Awareness, Usage, and Predictors for the Use of Doctor Rating Websites: Cross-Sectional Study in England. Journal of Medical Internet Research 2018;20(7):e243 View
  73. Nemzer L, Neymotin F. Concierge care and patient reviews. Health Economics 2020;29(8):913 View
  74. Oyebode O, Alqahtani F, Orji R. Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews. IEEE Access 2020;8:111141 View
  75. Shah A, Yan X, Shah S, Mamirkulova G. Mining patient opinion to evaluate the service quality in healthcare: a deep-learning approach. Journal of Ambient Intelligence and Humanized Computing 2020;11(7):2925 View
  76. Wagland R, Recio-Saucedo A, Simon M, Bracher M, Hunt K, Foster C, Downing A, Glaser A, Corner J. Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care. BMJ Quality & Safety 2016;25(8):604 View
  77. MacLaren R, Tran V, Chiappe D. Effects of motivation orientation on schoolwork enjoyment and achievement and study habits. Thinking Skills and Creativity 2017;24:199 View
  78. Sewalk K, Tuli G, Hswen Y, Brownstein J, Hawkins J. Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study. Journal of Medical Internet Research 2018;20(10):e10043 View
  79. Emmert M, Meier F, Heider A, Dürr C, Sander U. What do patients say about their physicians? An analysis of 3000 narrative comments posted on a German physician rating website. Health Policy 2014;118(1):66 View
  80. Farrington C, Stewart Z, Barnard K, Hovorka R, Murphy H. Experiences of closed‐loop insulin delivery among pregnant women with Type 1 diabetes. Diabetic Medicine 2017;34(10):1461 View
  81. Gabarron E, Larbi D, Dorronzoro E, Hasvold P, Wynn R, Årsand E. Factors Engaging Users of Diabetes Social Media Channels on Facebook, Twitter, and Instagram: Observational Study. Journal of Medical Internet Research 2020;22(9):e21204 View
  82. Jacobs M, Briley P, Ellis C. Quantifying Experiences with Telepractice for Aphasia Therapy: A Text Mining Analysis of Client Response Data. Seminars in Speech and Language 2020;41(05):414 View
  83. Lu Y, Pan T, Liu J, Wu J. Does Usage of Online Social Media Help Users With Depressed Symptoms Improve Their Mental Health? Empirical Evidence From an Online Depression Community. Frontiers in Public Health 2021;8 View
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  85. Bovonratwet P, Shen T, Islam W, Ast M, Haas S, Su E. Natural Language Processing of Patient-Experience Comments After Primary Total Knee Arthroplasty. The Journal of Arthroplasty 2021;36(3):927 View
  86. Bittar A, Velupillai S, Roberts A, Dutta R. Using General-purpose Sentiment Lexicons for Suicide Risk Assessment in Electronic Health Records: Corpus-Based Analysis. JMIR Medical Informatics 2021;9(4):e22397 View
  87. Sajid A, Awais M, Amir Mehmood M, Batool S, Shahzad A, Zafar A. Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry. EMITTER International Journal of Engineering Technology 2020:316 View
  88. Berkovic D, Ackerman I, Briggs A, Ayton D. Tweets by People With Arthritis During the COVID-19 Pandemic: Content and Sentiment Analysis. Journal of Medical Internet Research 2020;22(12):e24550 View
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  91. Shahat Osman A, Elragal A. Smart Cities and Big Data Analytics: A Data-Driven Decision-Making Use Case. Smart Cities 2021;4(1):286 View
  92. Langerhuizen D, Brown L, Doornberg J, Ring D, Kerkhoffs G, Janssen S. Analysis of Online Reviews of Orthopaedic Surgeons and Orthopaedic Practices Using Natural Language Processing. Journal of the American Academy of Orthopaedic Surgeons 2021;29(8):337 View
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  102. Chandra R, Kulkarni V. Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework. IEEE Access 2022;10:21291 View
  103. Jeong H, Bayro A, Umesh S, Mamgain K, Lee M. Social Media Users’ Perceptions of a Wearable Mixed Reality Headset During the COVID-19 Pandemic: Aspect-Based Sentiment Analysis. JMIR Serious Games 2022;10(3):e36850 View
  104. Silvera G. More Than Words: An Invited Commentary Regarding “Quantitative Patient-Reported Experience Measures Derived From Natural Language Processing Have a Normal Distribution and No Ceiling Effect”. Quality Management in Health Care 2022;31(4):219 View
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  108. A. Rahim A, Ibrahim M, Musa K, Chua S, Yaacob N. Assessing Patient-Perceived Hospital Service Quality and Sentiment in Malaysian Public Hospitals Using Machine Learning and Facebook Reviews. International Journal of Environmental Research and Public Health 2021;18(18):9912 View
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  111. Jain A, Bansal A, Tomar S. Aspect-Based Sentiment Analysis of Online Reviews for Business Intelligence. International Journal of Information Technologies and Systems Approach 2022;15(3):1 View
  112. Chandra R, Krishna A, Cotfas L. COVID-19 sentiment analysis via deep learning during the rise of novel cases. PLOS ONE 2021;16(8):e0255615 View
  113. Kalvesmaki A, Chapman A, Peterson K, Pugh M, Jones M, Gleason T. Analysis of a national response to a White House directive for ending veteran suicide. Health Services Research 2022;57(S1):32 View
  114. Bansal A, Kumar N. Aspect-Based Sentiment Analysis Using Attribute Extraction of Hospital Reviews. New Generation Computing 2022;40(4):941 View
  115. Chandra R, Saini R. Biden vs Trump: Modeling US General Elections Using BERT Language Model. IEEE Access 2021;9:128494 View
  116. Arias F, Zambrano Nunez M, Guerra-Adames A, Tejedor-Flores N, Vargas-Lombardo M. Sentiment Analysis of Public Social Media as a Tool for Health-Related Topics. IEEE Access 2022;10:74850 View
  117. Rey Velasco E, Pedersen H, Skinner T. Analysis of Patient Cues in Asynchronous Health Interactions: Pilot Study Combining Empathy Appraisal and Systemic Functional Linguistics. JMIR Formative Research 2022;6(12):e40058 View
  118. Wiegersma S, Hidajat M, Schrieken B, Veldkamp B, Olff M. Improving Web-Based Treatment Intake for Multiple Mental and Substance Use Disorders by Text Mining and Machine Learning: Algorithm Development and Validation. JMIR Mental Health 2022;9(4):e21111 View
  119. Khan A, Abbe A, Falissard B, Carita P, Bachert C, Mullol J, Reaney M, Chao J, Mannent L, Amin N, Mahajan P, Pirozzi G, Eckert L. Data Mining of Free-Text Responses: An Innovative Approach to Analyzing Patient Perspectives on Treatment for Chronic Rhinosinusitis with Nasal Polyps in a Phase IIa Proof-of-Concept Study for Dupilumab. Patient Preference and Adherence 2021;Volume 15:2577 View
  120. Osman A, Elragal A, Ståhlbröst A. Data-Driven Decisions in Smart Cities: A Digital Transformation Case Study. Applied Sciences 2022;12(3):1732 View
  121. Placona A, Rathert C. Are Online Patient Reviews Associated With Health Care Outcomes? A Systematic Review of the Literature. Medical Care Research and Review 2022;79(1):3 View
  122. Sukhera J, Ahmed H. Leveraging Machine Learning to Understand How Emotions Influence Equity Related Education: Quasi-Experimental Study. JMIR Medical Education 2022;8(1):e33934 View
  123. Gui L, He Y. Understanding patient reviews with minimum supervision. Artificial Intelligence in Medicine 2021;120:102160 View
  124. Oh S, Ji H, Kim J, Park E, del Pobil A. Deep learning model based on expectation-confirmation theory to predict customer satisfaction in hospitality service. Information Technology & Tourism 2022;24(1):109 View
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  126. Rahim A, Ibrahim M, Chua S, Musa K. Hospital Facebook Reviews Analysis Using a Machine Learning Sentiment Analyzer and Quality Classifier. Healthcare 2021;9(12):1679 View
  127. Vehviläinen-Julkunen K, Turpeinen S, Kvist T, Ryden-Kortelainen M, Nelimarkka S, Enshaeifar S, Faithfull S. Experience of Ambulatory Cancer Care. Cancer Nursing 2021;44(6):E331 View
  128. Chekijian S, Li H, Fodeh S. Emergency care and the patient experience: Using sentiment analysis and topic modeling to understand the impact of the COVID-19 pandemic. Health and Technology 2021;11(5):1073 View
  129. Meyer J, Okuboyejo S. User Reviews of Depression App Features: Sentiment Analysis. JMIR Formative Research 2021;5(12):e17062 View
  130. Khanbhai M, Warren L, Symons J, Flott K, Harrison-White S, Manton D, Darzi A, Mayer E. Using natural language processing to understand, facilitate and maintain continuity in patient experience across transitions of care. International Journal of Medical Informatics 2022;157:104642 View
  131. Alhur M, Alshamari S, Oláh J, Aldreabi H. Unsupervised Machine Learning to Identify Positive and Negative Themes in Jordanian mHealth Apps. International Journal of E-Services and Mobile Applications 2022;14(1):1 View
  132. Kumaresan C, Thangaraju P. Sentiment Analysis in Multiple Languages: A Review of Current Approaches and Challenges. REST Journal on Data Analytics and Artificial Intelligence 2023;2(1):8 View
  133. Lian R, Hsiao V, Hwang J, Ou Y, Robbins S, Connor N, Macdonald C, Sippel R, Sethares W, Schneider D. Predicting health-related quality of life change using natural language processing in thyroid cancer. Intelligence-Based Medicine 2023;7:100097 View
  134. Roche V, Robert J, Salam H. AI-Based Approach for Safety Signals Detection from Social Networks: Application to the Levothyrox Scandal in 2017 on Doctissimo Forum. SSRN Electronic Journal 2021 View
  135. Khaleghparast S, Maleki M, Hajianfar G, Soumari E, Oveisi M, Golandouz H, Noohi F, dehaki M, Golpira R, Mazloomzadeh S, Arabian M, Kalayinia S. Development of a patients’ satisfaction analysis system using machine learning and lexicon-based methods. BMC Health Services Research 2023;23(1) View
  136. Lian R, Hsiao V, Hwang J, Ou Y, Robbins S, Connor N, Macdonald C, Sippel R, Sethares W, Schneider D. Extracting Health-Related Quality of Life Information from Patient Language in Thyroid Cancer Using BERT. SSRN Electronic Journal 2022 View
  137. Salinari A, Machì M, Armas Diaz Y, Cianciosi D, Qi Z, Yang B, Ferreiro Cotorruelo M, Villar S, Dzul Lopez L, Battino M, Giampieri F. The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment. Diseases 2023;11(3):97 View
  138. Levett J, Elkaim L, Weber M, Yuh S, Lasry O, Alotaibi N, Georgiopoulos M, Berven S, Weil A. A twitter analysis of patient and family experience in pediatric spine surgery. Child's Nervous System 2023;39(12):3483 View
  139. Matsuda S, Ohtomo T, Okuyama M, Miyake H, Aoki K. Estimating Patient Satisfaction Through a Language Processing Model: Model Development and Evaluation. JMIR Formative Research 2023;7:e48534 View
  140. Yu H, Chiu Y, Wang J, Yu J, Hsu Y. Electronic consultation accessibility influence on patient assessments: A case–control study with user-generated tags of physician expertise. DIGITAL HEALTH 2023;9 View
  141. Noh Y, Kim M, Hong S. Identification of Emotional Spectrums of Patients Taking an Erectile Dysfunction Medication: Ontology-Based Emotion Analysis of Patient Medication Reviews on Social Media. Journal of Medical Internet Research 2023;25:e50152 View
  142. Niazi F, Elkaim L, Zadeh Khomami N, Levett J, Weil A, Hodaie M, Alotaibi N. Microvascular Decompression and Trigeminal Neuralgia: Patient Sentiment Analysis Using Natural Language Processing. World Neurosurgery 2023;180:e528 View
  143. Roche V, Robert J, Salam H. A holistic AI-based approach for pharmacovigilance optimization from patients behavior on social media. Artificial Intelligence in Medicine 2023;144:102638 View
  144. Chen J, Creamer G, Ning Y, Ben-Zvi T. Healthcare Sustainability: Hospitalization Rate Forecasting with Transfer Learning and Location-Aware News Analysis. Sustainability 2023;15(22):15840 View
  145. Lu K, Meaney C, Guo E, Leung F. Evaluating the Applicability of Existing Lexicon-Based Sentiment Analysis Techniques on Family Medicine Resident Feedback Field Notes: Retrospective Cohort Study. JMIR Medical Education 2023;9:e41953 View
  146. Yazdani A, Shamloo M, Khaki M, Nahvijou A. Use of sentiment analysis for capturing hospitalized cancer patients' experience from free-text comments in the Persian language. BMC Medical Informatics and Decision Making 2023;23(1) View
  147. Malhotra R, Reddy A, Jotwani R, Schatman M, Mehta N. Dishonest Physician Reviews: Challenging Physician Online Reviews and the Appeals Process. Journal of Medical Systems 2023;48(1) View
  148. Shi D, Zhang X, Liu L, Hansen P, Li X. Monetization of first questions by text mining: how do peer patients respond to online health information in a Q&A forum?. Aslib Journal of Information Management 2024 View
  149. Deahl Z, Banerjee I, Nadella M, Patel A, Dodoo C, Jaramillo I, Varner J, Nguyen E, Tan N. Sharing Patient Praises With Radiology Staff: Workflow Automation and Impact on Staff. Journal of the American College of Radiology 2023 View
  150. Powers C, Yang A, Verma H, Orloff J, Piontkowski A, Gulati N. Online Patient Attitudes Toward Cutaneous Immune-Related Adverse Events Attributed to Nivolumab and Pembrolizumab: Sentiment Analysis. JMIR Dermatology 2024;7:e53792 View
  151. Murray C, Mitchell L, Tuke J, Mackay M. Revealing patient-reported experiences in healthcare from social media using thedesign-acquire-process-model-analyse-visualise framework. DIGITAL HEALTH 2024;10 View
  152. Burt J, Newbould J, Abel G, Elliott M, Beckwith J, Llanwarne N, Elmore N, Davey A, Gibbons C, Campbell J, Roland M. Investigating the meaning of ‘good’ or ‘very good’ patient evaluations of care in English general practice: a mixed methods study. BMJ Open 2017;7(3):e014718 View

Books/Policy Documents

  1. Altrabsheh N, Kontonatsios G, Korkontzelos Y. Natural Language Processing and Information Systems. View
  2. Lamprinakos G, Aristeidopoulou I, Asanin S, Kapsalis A, Anadiotis A, Kaklamani D, Venieris I. Encyclopedia of E-Health and Telemedicine. View
  3. Abualigah L, Alfar H, Shehab M, Hussein A. Recent Advances in NLP: The Case of Arabic Language. View
  4. Carter P, Kondor K. Digital Extremisms. View
  5. Shah A, Yan X, Shah S, Khan S. Smart Health. View
  6. Xia C, Zhao D, Wang J, Liu J, Ma J. Smart Health. View
  7. Wang K, He C, Wang L, Wu J. Knowledge and Systems Sciences. View
  8. Tang M, Liu Y, Li Z, Liu Y. Intelligent Computing and Internet of Things. View
  9. Bernabé-Moreno J, Tejeda-Lorente A, Porcel C, Herrera-Viedma E. Advances in Fuzzy Logic and Technology 2017. View
  10. Parimbelli E, Quaglini S, Bellazzi R, Holmes J. Artificial Intelligence in Medicine. View
  11. Canbolat Z, Pinarbasi F. Exploring the Power of Electronic Word-of-Mouth in the Services Industry. View
  12. Luna-Aveiga H, Medina-Moreira J, Lagos-Ortiz K, Apolinario O, Paredes-Valverde M, del Pilar Salas-Zárate M, Valencia-García R. Advanced Computational Methods for Knowledge Engineering. View
  13. Rathi M, Jain N, Bist P, Agrawal T. High Performance Vision Intelligence. View
  14. Kushwah S, Kalra B, Das S. Computationally Intelligent Systems and their Applications. View
  15. Marisa Ferreira Gomes C, Paula Castro Amorim M, Jorge Ferreira Rodrigues M. e-Services. View
  16. Demner-Fushman D, Elhadad N, Friedman C. Biomedical Informatics. View
  17. Canbolat Z, Pinarbasi F. Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines. View
  18. Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. View
  19. Ranaldi L, Mastromattei M, Onorati D, Ruzzetti E, Fallucchi F, Zanzotto F. Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021. View
  20. Denecke K. Sentiment Analysis in the Medical Domain. View
  21. Dziczkowski G, Madyda G. Advances in Computational Collective Intelligence. View
  22. MacKay J, Wu S. Educational Principles and Practice in Veterinary Medicine. View
  23. Ahmad A, Mohamed A. Artificial Intelligence and Autoimmune Diseases. View