{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T11:04:53Z","timestamp":1782731093349,"version":"3.54.5"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T00:00:00Z","timestamp":1563235200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T00:00:00Z","timestamp":1563235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s12652-019-01399-8","type":"journal-article","created":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T17:03:03Z","timestamp":1563296583000},"page":"5309-5325","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["Sentiment analysis and text categorization of cancer medical records with LSTM"],"prefix":"10.1007","volume":"14","author":[{"given":"Deepak Chowdary","family":"Edara","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lakshmi Prasanna","family":"Vanukuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6861-6317","authenticated-orcid":false,"given":"Venkatramaphanikumar","family":"Sistla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Venkata Krishna Kishore","family":"Kolli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,7,16]]},"reference":[{"key":"1399_CR1","doi-asserted-by":"publisher","unstructured":"Aisopos F, Papadakis G, Varvarigou T (2011) Sentiment analysis of social media content using N-Gram graphs. In: Proceedings of the 3rd ACM SIGMM international workshop on Social media\u2014WSM\u201911, p\u00a09. https:\/\/doi.org\/10.1145\/2072609.2072614","DOI":"10.1145\/2072609.2072614"},{"issue":"5","key":"1399_CR2","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1097\/00007890-200203150-00016","volume":"73","author":"Y Ando","year":"2002","unstructured":"Ando Y, Terazaki H, Haraoka K, Tajiri T, Nakamura M, Obayashi K, Ishizaki T (2002) Presence of autoantibody against ATTR Val30Met after sequential liver transplantation. Transplantation 73(5):751\u2013755. https:\/\/doi.org\/10.1097\/00007890-200203150-00016","journal-title":"Transplantation"},{"key":"1399_CR3","first-page":"15","volume-title":"Lecture Notes in Computer Science","author":"ABAK Baltas","year":"2017","unstructured":"Baltas ABAK, Tsakalidis AK (2017) Algorithmic aspects of cloud computing. In: Lecture Notes in Computer Science, vol 10230. Springer, Berlin, pp 15\u201325"},{"key":"1399_CR4","unstructured":"Barry J (2017) Sentiment analysis of online reviews using bag-of-words and LSTM approaches. In: CEUR workshop proceedings, pp\u00a0272\u2013274"},{"key":"1399_CR5","doi-asserted-by":"publisher","unstructured":"Bashri MFA, Kusumaningrum R (2017) Sentiment analysis using Latent Dirichlet allocation and topic polarity wordcloud visualization. In: 2017 5th international conference on information and communication technology, ICoIC7 2017, 0(c), pp\u00a04\u20138. https:\/\/doi.org\/10.1109\/icoict.2017.8074651","DOI":"10.1109\/icoict.2017.8074651"},{"key":"1399_CR6","volume-title":"Professional development for cooperative learning: issues and approaches","year":"1998","unstructured":"Brody CM, Davidson N (eds) (1998) Professional development for cooperative learning: issues and approaches. Suny Press, New York"},{"issue":"12","key":"1399_CR7","doi-asserted-by":"publisher","first-page":"10533","DOI":"10.1016\/j.eswa.2012.02.120","volume":"39","author":"E Cambria","year":"2012","unstructured":"Cambria E, Benson T, Eckl C, Hussain A (2012) Sentic PROMs: application of sentic computing to the development of a novel unified framework for measuring health-care quality. Expert Syst Appl 39(12):10533\u201310543. https:\/\/doi.org\/10.1016\/j.eswa.2012.02.120","journal-title":"Expert Syst Appl"},{"issue":"1","key":"1399_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/jmlr.2003.3.4-5.951","volume":"12","author":"FA Carod","year":"1997","unstructured":"Carod FA, Cuadrado MP, Gonz\u00e1lez JG, Egido JH (1997) Autonomic disorder and sudden death in a patient with Wallenberg\u2019s syndrome. Neurolog\u00eda (Barcelona, Spain) 12(1):1\u20139. https:\/\/doi.org\/10.1162\/jmlr.2003.3.4-5.951","journal-title":"Neurolog\u00eda (Barcelona, Spain)"},{"issue":"1","key":"1399_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12889-017-4533-z","volume":"17","author":"Z Chen","year":"2017","unstructured":"Chen Z, Zeng DD (2017) Mining online e-liquid reviews for opinion polarities about e-liquid features. BMC Public Health 17(1):1\u20137. https:\/\/doi.org\/10.1186\/s12889-017-4533-z","journal-title":"BMC Public Health"},{"key":"1399_CR102","unstructured":"Chen J, Pan X, Monga R, Bengio S, Jozefowicz R (2016) Revisiting distributed synchronous SGD. arXiv preprint arXiv:1604.00981"},{"issue":"c","key":"1399_CR10","doi-asserted-by":"publisher","first-page":"8869","DOI":"10.1109\/access.2017.2694446","volume":"5","author":"M Chen","year":"2017","unstructured":"Chen M, Hao Y, Hwang K, Wang L, Wang L (2017a) Disease prediction by machine learning over big data from healthcare communities. IEEE Access 5(c):8869\u20138879. https:\/\/doi.org\/10.1109\/access.2017.2694446","journal-title":"IEEE Access"},{"key":"1399_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.10.065","author":"T Chen","year":"2017","unstructured":"Chen T, Xu R, He Y, Wang X (2017b) Improving sentiment analysis via sentence type classification using BiLSTM-CRF and CNN. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2016.10.065","journal-title":"Expert Syst Appl"},{"issue":"3","key":"1399_CR12","doi-asserted-by":"publisher","first-page":"189","DOI":"10.4236\/jcc.2015.35024","volume":"3","author":"OKM Cheng","year":"2015","unstructured":"Cheng OKM, Lau R (2015) Big data stream analytics for near real-time sentiment analysis. J Comput Commun 3(3):189\u2013195. https:\/\/doi.org\/10.4236\/jcc.2015.35024","journal-title":"J Comput Commun"},{"key":"1399_CR13","doi-asserted-by":"publisher","unstructured":"Chiu B, Crichton G, Korhonen A, Pyysalo S (2016) How to train good word embeddings for biomedical NLP. In: Proceedings of the 15th workshop on biomedical natural language processing, pp\u00a0166\u2013174. https:\/\/doi.org\/10.18653\/v1\/w16-2922","DOI":"10.18653\/v1\/w16-2922"},{"issue":"2","key":"1399_CR14","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1016\/j.jss.2016.06.050","volume":"206","author":"WC Crannell","year":"2016","unstructured":"Crannell WC, Clark E, Jones C, James TA, Moore J (2016) A pattern-matched Twitter analysis of US cancer-patient sentiments. J Surg Res 206(2):536\u2013542. https:\/\/doi.org\/10.1016\/j.jss.2016.06.050(Elsevier Inc)","journal-title":"J Surg Res"},{"issue":"6","key":"1399_CR15","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1089\/tmj.2011.0227","volume":"18","author":"I De la Torre-D\u00edez","year":"2012","unstructured":"De la Torre-D\u00edez I, D\u00edaz-Pernas FJ, Ant\u00f3n-Rodr\u00edguez M (2012) A content analysis of chronic diseases social groups on facebook and twitter. Telemed e-Health 18(6):404\u2013408. https:\/\/doi.org\/10.1089\/tmj.2011.0227","journal-title":"Telemed e-Health"},{"issue":"12","key":"1399_CR16","doi-asserted-by":"publisher","first-page":"1870","DOI":"10.1016\/j.ins.2009.01.025","volume":"179","author":"K Denecke","year":"2009","unstructured":"Denecke K, Nejdl W (2009) How valuable is medical social media data? Content analysis of the medical web. Inf Sci 179(12):1870\u20131880. https:\/\/doi.org\/10.1016\/j.ins.2009.01.025(Elsevier Inc)","journal-title":"Inf Sci"},{"issue":"5","key":"1399_CR17","doi-asserted-by":"publisher","first-page":"2570","DOI":"10.3906\/elk-1704-178","volume":"26","author":"KA Devi","year":"2018","unstructured":"Devi KA, Edara DC, Sistla VPK, Kolli VKK (2018) Extended correlated principal component analysis with SVM-PUK in opinion mining. Turk J Electr Eng Comput Sci 26(5):2570\u20132582. https:\/\/doi.org\/10.3906\/elk-1704-178","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"1399_CR18","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.eswa.2018.03.004","volume":"103","author":"A Dey","year":"2018","unstructured":"Dey A, Jenamani M, Thakkar JJ (2018) Senti-N-Gram: an n-gram lexicon for sentiment analysis. Expert Syst Appl 103:92\u2013105. https:\/\/doi.org\/10.1016\/j.eswa.2018.03.004(Elsevier Ltd)","journal-title":"Expert Syst Appl"},{"issue":"1","key":"1399_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13326-017-0120-6","volume":"8","author":"J Du","year":"2017","unstructured":"Du J, Xu J, Song H, Liu X, Tao C (2017) Optimization on machine learning based approaches for sentiment analysis on HPV vaccines related tweets. J Biomed Semant 8(1):1\u20137. https:\/\/doi.org\/10.1186\/s13326-017-0120-6","journal-title":"J Biomed Semant"},{"key":"1399_CR20","unstructured":"Esuli A, Sebastiani F (2006) Determining term subjectivity and term orientation for opinion mining. In: Proceedings of the 11th meeting of the european chapter of the association for computational linguistics (EACL-2006), vol\u00a02(1), pp\u00a0193\u2013200. http:\/\/doi.org\/10.1.1.60.8645"},{"issue":"1","key":"1399_CR21","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/s40537-015-0015-2","volume":"2","author":"X Fang","year":"2015","unstructured":"Fang X, Zhan J (2015) Sentiment analysis using product review data. J Big Data 2(1):5. https:\/\/doi.org\/10.1186\/s40537-015-0015-2","journal-title":"J Big Data"},{"key":"1399_CR22","doi-asserted-by":"publisher","unstructured":"Ficek M, Kencl L (2012) Inter-call mobility model: a spatio-temporal refinement of call data records using a gaussian mixture model. In: 2012 Proceedings IEEE INFOCOM. IEEE, pp\u00a0469\u2013477. https:\/\/doi.org\/10.1109\/infcom.2012.6195786","DOI":"10.1109\/infcom.2012.6195786"},{"key":"1399_CR23","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/417502","author":"I Ha","year":"2015","unstructured":"Ha I, Back B, Ahn B (2015) MapReduce functions to analyze sentiment information from social big data. Int J Distrib Sens Netw. https:\/\/doi.org\/10.1155\/2015\/417502","journal-title":"Int J Distrib Sens Netw"},{"key":"1399_CR24","doi-asserted-by":"publisher","unstructured":"Hamdan H, Bellot P, Bechet F (2015) Lsislif: CRF and logistic regression for opinion target extraction and sentiment polarity analysis. In: Proceedings of the 9th international workshop on semantic evaluation, (SemEval), pp\u00a0753\u2013758. https:\/\/doi.org\/10.1016\/j.crhy.2009.03.001","DOI":"10.1016\/j.crhy.2009.03.001"},{"issue":"1","key":"1399_CR25","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/2041-1480-3-2","volume":"3","author":"S Jonnalagadda","year":"2012","unstructured":"Jonnalagadda S, Peeler R, Topham P (2012) Discovering opinion leaders for medical topics using news articles. J Biomed Semant 3(1):2","journal-title":"J Biomed Semant"},{"issue":"5","key":"1399_CR26","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1002\/pon.1942","volume":"21","author":"E Kim","year":"2012","unstructured":"Kim E, Han JY, Moon TJ, Shaw B, Shah DV, McTavish FM, Gustafson DH (2012) The process and effect of supportive message expression and reception in online breast cancer support groups. Psycho-Oncology 21(5):531\u2013540. https:\/\/doi.org\/10.1002\/pon.1942","journal-title":"Psycho-Oncology"},{"key":"1399_CR27","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1016\/j.procs.2014.05.296","volume":"31","author":"J Liang","year":"2014","unstructured":"Liang J, Liu P, Tan J, Bai S (2014) Sentiment classification based on AS-LDA model. Proc Comput Sci 31:511\u2013516. https:\/\/doi.org\/10.1016\/j.procs.2014.05.296","journal-title":"Proc Comput Sci"},{"key":"1399_CR28","doi-asserted-by":"publisher","unstructured":"Liang X, Lin L, Shen X, Feng J, Yan S, Xing EP (2017) Interpretable structure-evolving LSTM. In: Proceedings\u201430th IEEE conference on computer vision and pattern recognition, CVPR 2017, 2017-Janua, pp\u00a02175\u20132184. https:\/\/doi.org\/10.1109\/cvpr.2017.234","DOI":"10.1109\/cvpr.2017.234"},{"issue":"22","key":"1399_CR29","doi-asserted-by":"publisher","first-page":"14203","DOI":"10.1007\/s11042-016-3363-9","volume":"75","author":"F Lin","year":"2016","unstructured":"Lin F, Xiahou J, Xu Z (2016) TCM clinic records data mining approaches based on weighted-LDA and multi-relationship LDA model. Multimed Tools Appl 75(22):14203\u201314232. https:\/\/doi.org\/10.1007\/s11042-016-3363-9","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"1399_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2193-1801-2-309","volume":"2","author":"Y Lu","year":"2013","unstructured":"Lu Y (2013) Automatic topic identification of health-related messages in online health community using text classification. SpringerPlus 2(1):1\u20137. https:\/\/doi.org\/10.1186\/2193-1801-2-309","journal-title":"SpringerPlus"},{"key":"1399_CR31","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-018-1212-z","author":"Y Madani","year":"2018","unstructured":"Madani Y, Erritali M, Bengourram J (2018) Sentiment analysis using semantic similarity and Hadoop MapReduce. Knowl Inf Syst. https:\/\/doi.org\/10.1007\/s10115-018-1212-z(Springer London)","journal-title":"Knowl Inf Syst"},{"issue":"4","key":"1399_CR32","doi-asserted-by":"publisher","first-page":"4379","DOI":"10.1007\/s11042-017-5515-y","volume":"77","author":"G Manogaran","year":"2018","unstructured":"Manogaran G, Varatharajan R, Priyan MK (2018) Hybrid recommendation system for heart disease diagnosis based on multiple kernel learning with adaptive neuro-fuzzy inference system. Multimed Tools Appl 77(4):4379\u20134399. https:\/\/doi.org\/10.1007\/s11042-017-5515-y","journal-title":"Multimed Tools Appl"},{"key":"1399_CR33","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/S0043-1354(01)00016-1","volume":"6","author":"P Meesad","year":"2011","unstructured":"Meesad P, Boonrawd P, Nuipian V (2011) A Chi square-test for word importance differentiation in text classification. Int Conf Inf Electron Eng 6:110\u2013114. https:\/\/doi.org\/10.1016\/S0043-1354(01)00016-1","journal-title":"Int Conf Inf Electron Eng"},{"key":"1399_CR34","doi-asserted-by":"publisher","first-page":"584","DOI":"10.3233\/978-1-61499-432-9-584","volume":"205","author":"JA Minarro-Gimenez","year":"2014","unstructured":"Minarro-Gimenez JA, Marin-Alonso O, Samwald M (2014) Exploring the application of deep learning techniques on medical text corpora. Stud Health Technol Inform 205:584\u2013588. https:\/\/doi.org\/10.3233\/978-1-61499-432-9-584","journal-title":"Stud Health Technol Inform"},{"key":"1399_CR35","unstructured":"Miura Y, Hattori K, Ohkuma T, Masuichi H (2013) Topic modeling with sentiment clues and relaxed labeling schema. In: Proceedings of the 3rd workshop on sentiment analysis where AI meets psychology, pp\u00a06\u201314"},{"key":"1399_CR36","doi-asserted-by":"publisher","first-page":"205520761665767","DOI":"10.1177\/2055207616657670","volume":"2","author":"D Murthy","year":"2016","unstructured":"Murthy D, Eldredge M (2016) Who tweets about cancer? An analysis of cancer-related tweets in the USA. Digit Health 2:205520761665767. https:\/\/doi.org\/10.1177\/2055207616657670","journal-title":"Digit Health"},{"key":"1399_CR37","unstructured":"Nodarakis N, Sioutas S, Tsakalidis AK, Tzimas G (2016) Large scale sentiment analysis on twitter with spark. In: EDBT\/ICDT workshops, pp\u00a01\u20138"},{"issue":"3","key":"1399_CR38","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/MCI.2016.2572540","volume":"11","author":"L Oneto","year":"2016","unstructured":"Oneto L, Bisio F, Cambria E, Anguita D (2016) Statistical learning theory and ELM for big social data analysis. IEEE Comput Intell Mag 11(3):45\u201355. https:\/\/doi.org\/10.1109\/MCI.2016.2572540","journal-title":"IEEE Comput Intell Mag"},{"issue":"3","key":"1399_CR39","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/j.cmpb.2011.03.018","volume":"104","author":"A Ozcift","year":"2011","unstructured":"Ozcift A, Gulten A (2011) Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms. Comput Methods Programs Biomed 104(3):443\u2013451. https:\/\/doi.org\/10.1016\/j.cmpb.2011.03.018(Elsevier Ireland Ltd)","journal-title":"Comput Methods Programs Biomed"},{"issue":"1\u20132","key":"1399_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/1500000011","volume":"2","author":"B Pang","year":"2008","unstructured":"Pang B, Lee L (2008) Opinion mining and sentiment analysis. Found Trends Inf Retr 2(1\u20132):1\u2013135. https:\/\/doi.org\/10.1561\/1500000011","journal-title":"Found Trends Inf Retr"},{"key":"1399_CR41","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1093\/jncimonographs\/lgt025","volume":"47","author":"K Portier","year":"2013","unstructured":"Portier K, Greer GE, Rokach L, Ofek N, Wang Y, Biyani P, Yu M, Banerjee S, Zhao K, Mitra P, Yen J (2013) Understanding topics and sentiment in an online cancer survivor community. J Natl Cancer Inst Monogr 47:195\u2013198. https:\/\/doi.org\/10.1093\/jncimonographs\/lgt025","journal-title":"J Natl Cancer Inst Monogr"},{"key":"1399_CR42","doi-asserted-by":"publisher","unstructured":"Qiu B, Zhao K, Mitra P, Wu D, Caragea C, Yen J, Portier K (2011) Get online support, feel better-sentiment analysis and dynamics in an online cancer survivor community. In: Proceedings\u20142011 IEEE international conference on privacy, security, risk and trust and IEEE international conference on social computing, PASSAT\/SocialCom 2011, pp\u00a0274\u2013281. https:\/\/doi.org\/10.1109\/passat\/socialcom.2011.127","DOI":"10.1109\/passat\/socialcom.2011.127"},{"key":"1399_CR43","doi-asserted-by":"publisher","unstructured":"Rahnama AHA (2014) Distributed real-time sentiment analysis for big data social streams. In: Proceedings\u20142014 international conference on control, decision and information technologies, CoDIT 2014, pp\u00a0789\u2013794. https:\/\/doi.org\/10.1109\/codit.2014.6996998","DOI":"10.1109\/codit.2014.6996998"},{"key":"1399_CR44","doi-asserted-by":"publisher","unstructured":"TH M, Sahu S, Anand A (2015) Evaluating distributed word representations for capturing semantics of biomedical concepts. In: Proceedings of BioNLP 15, (Ml), pp\u00a0158\u2013163. https:\/\/doi.org\/10.18653\/v1\/w15-3820","DOI":"10.18653\/v1\/w15-3820"},{"issue":"2","key":"1399_CR45","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1080\/108107300406866","volume":"5","author":"BR Shaw","year":"2000","unstructured":"Shaw BR, McTavish F, Hawkins R, Gustafson DH, Pingree S (2000) Experiences of women with breast cancer: exchanging social support over the CHESS computer network. J Health Commun 5(2):135\u2013159. https:\/\/doi.org\/10.1080\/108107300406866","journal-title":"J Health Commun"},{"key":"1399_CR46","series-title":"Lecture notes in computer science","volume-title":"ext, speech, and dialogue. TSD 2013","author":"D Soutner","year":"2013","unstructured":"Soutner D, M\u00fcller L (2013) Application of LSTM neural networks in language modelling. In: Habernal I, Matou\u0161ek V (eds) Text, speech, and dialogue. TSD 2013, Lecture notes in computer science, vol\u00a08082. Springer, Berlin"},{"key":"1399_CR47","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-018-0451-2","author":"D Spinczyk","year":"2018","unstructured":"Spinczyk D, Nabrdalik K, Rojewska K (2018) Computer aided sentiment analysis of anorexia nervosa patients\u2019 vocabulary. BioMed Eng Online BioMed Cent. https:\/\/doi.org\/10.1186\/s12938-018-0451-2","journal-title":"BioMed Eng Online BioMed Cent"},{"key":"1399_CR48","doi-asserted-by":"publisher","unstructured":"Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2015) Going deeper with convolutions. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition, 07-12-June, pp\u00a01\u20139. https:\/\/doi.org\/10.1109\/cvpr.2015.7298594","DOI":"10.1109\/cvpr.2015.7298594"},{"key":"1399_CR49","first-page":"171","volume":"49","author":"T Timusk","year":"1995","unstructured":"Timusk T, Holmes CC, Reichardt W (1995) C-axis properties of 123, like Lanl-Cm95. Anharmonic Prop High-T_c Cuprates 49:171","journal-title":"Anharmonic Prop High-T_c Cuprates"},{"issue":"7055","key":"1399_CR50","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1136\/bmj.313.7055.438","volume":"313","author":"A Tonks","year":"1996","unstructured":"Tonks A, Smith R (1996) Information in practice. BMJ (Clin Res Ed.) 313(7055):438. https:\/\/doi.org\/10.1136\/bmj.313.7055.438","journal-title":"BMJ (Clin Res Ed.)"},{"key":"1399_CR51","doi-asserted-by":"publisher","first-page":"S164","DOI":"10.1016\/j.jbi.2015.08.011","volume":"58","author":"M Torii","year":"2015","unstructured":"Torii M, Fan JW, Yang WL, Lee T, Wiley MT, Zisook DS, Huang Y (2015) Risk factor detection for heart disease by applying text analytics in electronic medical records. J Biomed Inform 58:S164\u2013S170. https:\/\/doi.org\/10.1016\/j.jbi.2015.08.011(Elsevier Inc)","journal-title":"J Biomed Inform"},{"key":"1399_CR52","doi-asserted-by":"publisher","unstructured":"Underhill DG, McDowell LK, Marchette DJ, Solka JL (2007) Enhancing text analysis via dimensionality reduction. In: 2007 IEEE international conference on information reuse and integration, IEEE IRI-2007, vol\u00a021402(410), pp\u00a0348\u2013353. https:\/\/doi.org\/10.1109\/iri.2007.4296645","DOI":"10.1109\/iri.2007.4296645"},{"issue":"3","key":"1399_CR53","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s40012-014-0055-3","volume":"2","author":"G Vinodhini","year":"2014","unstructured":"Vinodhini G, Chandrasekaran RM (2014) Opinion mining using principal component analysis based ensemble model for e-commerce application. CSI Trans ICT 2(3):169\u2013179. https:\/\/doi.org\/10.1007\/s40012-014-0055-3","journal-title":"CSI Trans ICT"},{"key":"1399_CR54","doi-asserted-by":"publisher","unstructured":"Vinodhini G, Chandrasekaran RM (2015) Sentiment classification using principal component analysis based neural network model. In: 2014 International conference on information communication and embedded systems, ICICES 2014, vol\u00a0978, pp\u00a01\u20136. https:\/\/doi.org\/10.1109\/icices.2014.7033961","DOI":"10.1109\/icices.2014.7033961"},{"key":"1399_CR55","doi-asserted-by":"publisher","unstructured":"Vittayakorn S, Umeda T, Murasaki K, Sudo K, Okatani T, Yamaguchi K (2016) Automatic attribute discovery with neural activations, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9908 LNCS, pp\u00a0252\u2013268. https:\/\/doi.org\/10.1007\/978-3-319-46493-0_16","DOI":"10.1007\/978-3-319-46493-0_16"},{"issue":"7351","key":"1399_CR100","doi-asserted-by":"publisher","first-page":"1434","DOI":"10.1136\/bmj.324.7351.1434","volume":"324","author":"P Whitten","year":"2002","unstructured":"Whitten P, Mair F, Haycox A, May C, Williams L, Hellmich S (2002) Systematic review of cost effectiveness studies of telemedicine interventions. BMJ 324(7351):1434\u20131437","journal-title":"BMJ"},{"key":"1399_CR56","doi-asserted-by":"publisher","unstructured":"Xia L, Gentile AL, Munro J, Iria J (2009) Improving patient opinion mining through multi-step classification. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5729 LNAI, pp\u00a070\u201376. https:\/\/doi.org\/10.1007\/978-3-642-04208-9_13","DOI":"10.1007\/978-3-642-04208-9_13"},{"key":"1399_CR57","doi-asserted-by":"crossref","unstructured":"Yan X, Wu X, Kakadiaris IA, Shah SK (2012) To track or to detect? An ensemble framework for optimal selection. In: Fitzgibbon A, Lazebnik S, Perona P, Sato Y, Schmid C (eds) Computer vision\u2014ECCV 2012. Lecture Notes in Computer Science, vol\u00a075\/76. Springer, Berlin","DOI":"10.1007\/978-3-642-33715-4_43"},{"key":"1399_CR58","doi-asserted-by":"publisher","unstructured":"Yu R, Li A, Morariu VI, Davis LS (2017) Visual relationship detection with internal and external linguistic knowledge distillation. In: Proceedings of the IEEE international conference on computer vision, 2017-Octob(1), pp\u00a01068\u20131076. https:\/\/doi.org\/10.1109\/iccv.2017.121","DOI":"10.1109\/iccv.2017.121"},{"issue":"e2","key":"1399_CR59","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1136\/amiajnl-2013-002282","volume":"21","author":"K Zhao","year":"2014","unstructured":"Zhao K, Yen J, Greer G, Qiu B, Mitra P, Portier K (2014) Finding influential users of online health communities: a new metric based on sentiment influence. J Am Med Inform Assoc JAMIA 21(e2):1. https:\/\/doi.org\/10.1136\/amiajnl-2013-002282","journal-title":"J Am Med Inform Assoc JAMIA"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01399-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-019-01399-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01399-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T12:12:18Z","timestamp":1684843938000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-019-01399-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,16]]},"references-count":61,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["1399"],"URL":"https:\/\/doi.org\/10.1007\/s12652-019-01399-8","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,16]]},"assertion":[{"value":"7 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}