乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T04:22:23Z","timestamp":1727065343649},"reference-count":24,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,1,23]],"date-time":"2021-01-23T00:00:00Z","timestamp":1611360000000},"content-version":"vor","delay-in-days":22,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Procedia Computer Science"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1016\/j.procs.2021.01.194","type":"journal-article","created":{"date-parts":[[2021,2,23]],"date-time":"2021-02-23T01:58:25Z","timestamp":1614045505000},"page":"487-494","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":9,"special_numbering":"C","title":["Wavelet-based cancer drug recommender system"],"prefix":"10.1016","volume":"181","author":[{"given":"Liliana","family":"Brand\u00e3o","sequence":"first","affiliation":[]},{"given":"Fernando Paulo","family":"Belfo","sequence":"additional","affiliation":[]},{"given":"Alexandre","family":"Silva","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.procs.2021.01.194_bib1","series-title":"Recommender Systems Handbook","author":"Ricci","year":"2011"},{"key":"10.1016\/j.procs.2021.01.194_bib2","unstructured":"A. Sei\u00e7a, A. Trigo, and F. P. Belfo, \u201cLexiNB - Uma Abordagem Biet\u00e1pica de Classifica\u00e7\u00e3o de Sentimentos em Tweets Relacionados com as Autoridades Fiscais Portuguesas,\u201d in Proceedings of the 19.a Confer\u00eancia da Associa\u00e7\u00e3o Portuguesa de Sistemas de Informa\u00e7\u00e3o (CAPSI\u20192019) held in Lisboa, Portugal, 11-12 October 2019. Paper 5., 2019."},{"key":"10.1016\/j.procs.2021.01.194_bib3","unstructured":"C. Pimenta, R. Ribeiro, V. S\u00e1, and F. P. Belfo, \u201cFatores que Influenciam o Sucesso Escolar das Licenciaturas numa Institui\u00e7\u00e3o de Ensino Superior Portuguesa,\u201d in 18a Confer\u00eancia da Associa\u00e7\u00e3o Portuguesa de Sistemas de Informa\u00e7\u00e3o (CAPSI 2018) Associa\u00e7\u00e3o Portuguesa de Sistemas de Informa\u00e7\u00e3o: Santar\u00e9m, Portugal, 2018."},{"issue":"1-2","key":"10.1016\/j.procs.2021.01.194_bib4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0933-3657(02)00049-0","article-title":"\u201cUniqueness of medical data mining,\u201d","volume":"26","author":"Cios","year":"2002","journal-title":"Artif. Intell. Med."},{"issue":"4","key":"10.1016\/j.procs.2021.01.194_bib5","first-page":"597","article-title":"\u201cMachine learning for direct marketing response models: Bayesian networks with evolutionary programming,\u201d","volume":"52","author":"Cui, M. L. Wong","year":"2006","journal-title":"Manage. Sci."},{"issue":"3","key":"10.1016\/j.procs.2021.01.194_bib6","first-page":"3","article-title":"\u201cUsing machine learning to predict future tv ratings,\u201d","volume":"1","author":"Sereday","year":"2017","journal-title":"Data Sci. Nielsen"},{"key":"10.1016\/j.procs.2021.01.194_bib7","unstructured":"F. Loureiro, A., Louren\u00e7o, J., Costa, E., Belfo, \u201cIndu\u00e7\u00e3o de \u00c1rvores de Decis\u00e3o na Descoberta de Conhecimento: Caso de Empresa de Organiza\u00e7\u00e3o de Eventos,\u201d in VI Congresso Internacional de Casos Docentes em Marketing P\u00fablico e N\u00e3o Lucrativo, 2014."},{"issue":"3","key":"10.1016\/j.procs.2021.01.194_bib8","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.cell.2016.06.017","article-title":"\u201cA landscape of pharmacogenomic interactions in cancer,\u201d","volume":"166","author":"Iorio et al","year":"2016","journal-title":"Cell"},{"issue":"5","key":"10.1016\/j.procs.2021.01.194_bib9","first-page":"553","volume":"19","author":"Serra","year":"2003","journal-title":"\u201cAutomatic analysis of DNA microarray images using mathematical morphology,\u201d"},{"issue":"1","key":"10.1016\/j.procs.2021.01.194_bib10","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/34.745739","article-title":"\u201cFeature extraction from wavelet coefficients for pattern recognition tasks,\u201d","volume":"21","author":"Pittner","year":"1999","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.procs.2021.01.194_bib11","doi-asserted-by":"crossref","unstructured":"J. C. Costello et al., \u201cA community effort to assess and improve drug sensitivity prediction algorithms,\u201d no. June, 2014.","DOI":"10.1038\/nbt.2877"},{"issue":"March","key":"10.1016\/j.procs.2021.01.194_bib12","first-page":"2808","volume":"34","author":"He, L. Folkman","year":"2018","journal-title":"\u201cKernelized rank learning for personalized drug recommendation,\u201d"},{"key":"10.1016\/j.procs.2021.01.194_bib13","doi-asserted-by":"crossref","first-page":"13338","DOI":"10.1109\/ACCESS.2019.2891759","article-title":"\u201cWavelet Denoising Algorithm Based on NDOA Compressed Sensing for Fluorescence Image of Microarray,\u201d","volume":"7","author":"Gan et al","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.procs.2021.01.194_bib14","series-title":"The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance","author":"Addison","year":"2017"},{"key":"10.1016\/j.procs.2021.01.194_bib15","doi-asserted-by":"crossref","unstructured":"J. Wan and S. Zhou, \u201cFeatures extraction based on wavelet packet transform for B-mode ultrasound liver images,\u201d Proc. - 2010 3rd Int. Congr. Image Signal Process. CISP 2010, vol. 2, pp. 949\u2013955, 2010.","DOI":"10.1109\/CISP.2010.5646917"},{"key":"10.1016\/j.procs.2021.01.194_bib16","first-page":"1","article-title":"\u201cClassification of Chest Diseases using Wavelet Transforms and Transfer Learning,\u201d","author":"Rasheed, M. S. Younis","year":"2020","journal-title":"Micad"},{"key":"10.1016\/j.procs.2021.01.194_bib17","unstructured":"S. Li, C. Liao, and J. T. Kwok, \u201cWavelet-Based Feature Extraction for Microarray Data Classification Wavelet-Based Feature Extraction for Microarray Data Classification,\u201d no. May 2014, 2006."},{"issue":"1","key":"10.1016\/j.procs.2021.01.194_bib18","doi-asserted-by":"crossref","first-page":"990","DOI":"10.1016\/j.eswa.2010.07.104","article-title":"\u201cWavelet selection for disease classification by DNA microarray data,\u201d","volume":"38","author":"Nanni","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.procs.2021.01.194_bib19","series-title":"Recommender Systems - The Textbook","author":"Aggarwal","year":"2016"},{"key":"10.1016\/j.procs.2021.01.194_bib20","unstructured":"C. Suphavilai, D. Bertrand, and N. Nagarajan, \u201cPredicting Cancer Drug Response using a Recommender System,\u201d vol. 34, no. June, pp. 3907\u20133914, 2018."},{"issue":"4","key":"10.1016\/j.procs.2021.01.194_bib21","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"\u201cImage quality assessment: from error visibility to structural similarity,\u201d","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. image Process."},{"key":"10.1016\/j.procs.2021.01.194_bib22","unstructured":"C. Properties, M. P. Menden, F. Iorio, M. Garnett, U. Mcdermott, and C. H. Benes, \u201cMachine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties,\u201d no. April, 2013."},{"key":"10.1016\/j.procs.2021.01.194_bib23","unstructured":"Google, \u201cGoogle Colaboratory,\u201d 2020. [Online]. Available: https:\/\/colab.research.google.com\/. [Accessed: 28-Jan-2020]."},{"issue":"4","key":"10.1016\/j.procs.2021.01.194_bib24","first-page":"1108","volume":"56","author":"Liu","year":"2009","journal-title":"\u201cFind Significant Gene Information Based on Changing Points of Microarray Data,\u201d"}],"container-title":["Procedia Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050921002362?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050921002362?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T09:15:28Z","timestamp":1615886128000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877050921002362"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":24,"alternative-id":["S1877050921002362"],"URL":"https:\/\/doi.org\/10.1016\/j.procs.2021.01.194","relation":{},"ISSN":["1877-0509"],"issn-type":[{"value":"1877-0509","type":"print"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Wavelet-based cancer drug recommender system","name":"articletitle","label":"Article Title"},{"value":"Procedia Computer Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.procs.2021.01.194","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}