LEADER 05230 am 22007813u 450 001 9910293143703321 005 20230125211840.0 010 $a3-319-78503-6 024 7 $a10.1007/978-3-319-78503-5 035 $a(CKB)4100000004243864 035 $a(DE-He213)978-3-319-78503-5 035 $a(MiAaPQ)EBC5394754 035 $a(Au-PeEL)EBL5394754 035 $a(OCoLC)1078960705 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/57605 035 $a(PPN)227406605 035 $a(EXLCZ)994100000004243864 100 $a20180514d2018 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aClinical Text Mining$b[electronic resource] $eSecondary Use of Electronic Patient Records /$fby Hercules Dalianis 205 $a1st ed. 2018. 210 $cSpringer Nature$d2018 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XVII, 181 p. 54 illus., 28 illus. in color.) 311 $a3-319-78502-8 327 $aIntroduction -- The history of the patient record and the paper record -- User needs: clinicians, clinical researchers and hospital management -- Characteristics of patient records and clinical corpora -- Medical classifications and terminologies -- Evaluation metrics and evaluation -- Basic building blocks for clinical text processing -- Computational methods for text analysis and text classification -- Ethics and privacy of patient records for clinical text mining research -- Applications of clinical text mining -- Networks and shared tasks in clinical text mining -- Conclusions and outlook -- References -- Index. 330 $aThis open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book?s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields. 606 $aInformation storage and retrieval 606 $aHealth informatics 606 $aNatural language processing (Computer science) 606 $aData mining 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 610 $aNatural Language Processing 610 $aText Analysis 610 $aData Mining 610 $aHealth Informatics 610 $aText Mining 610 $aMedical Terminologies 610 $aHealth Care Information Systems 610 $aSupport Vector Machines 615 0$aInformation storage and retrieval. 615 0$aHealth informatics. 615 0$aNatural language processing (Computer science). 615 0$aData mining. 615 14$aInformation Storage and Retrieval. 615 24$aHealth Informatics. 615 24$aNatural Language Processing (NLP). 615 24$aHealth Informatics. 615 24$aNatural Language Processing (NLP). 615 24$aData Mining and Knowledge Discovery. 676 $a025.04 700 $aDalianis$b Hercules$4aut$4http://id.loc.gov/vocabulary/relators/aut$0994610 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910293143703321 996 $aClinical Text Mining$92277695 997 $aUNINA LEADER 03959 am 2200733 n 450 001 9910576798703321 005 20211214 010 $a2-493207-00-9 024 7 $a10.4000/books.africae.3552 035 $a(CKB)4100000012877770 035 $a(FrMaCLE)OB-africae-3552 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/87155 035 $a(PPN)263750957 035 $a(EXLCZ)994100000012877770 100 $a20220621j|||||||| ||| 0 101 0 $apor 135 $auu||||||m|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRenegociar a Centralidade do Estado em Moçambique $eMunicipalização na Beira, em Mueda e em Quissico /$fEgídio Guambe 210 $aMaputo $cAfricae$d2021 215 $a1 online resource (328 p.) 225 1 $aAfricae Monographs 311 $a989-20-9793-9 330 $aNos últimos anos tanto os Estados do Sul como os do Norte empenharam-se em sucessivas reformas administrativas que parecem seguir os mesmos modelos. A maior parte das leituras destes processos, no que se refere aos países do Sul, nomeadamente os africanos, persistem em invocar o seu carácter de imposição a que os doadores os submetem. Sem que se faça uma verdadeira análise a nível local e sem estudos aprofundados, estas reformas têm sido apresentadas grosso modo como fracassos. Este trabalho pretende por isso contribuir para uma leitura crítica da sua execução e das práticas resultantes da respectiva aprendizagem, como modos de exercício do poder. A partir de uma reconstituição empírica da implementação das medidas de descentralização, através do funcionamento dos municípios da cidade da Beira e das vilas de Mueda e Quissico, este livro pretende mostrar que a aprendizagem de uma reforma é influenciada pela historicidade das relações entre Estado e sociedade dentro do espaço da sua execução. Combinando diversas abordagens de sociologia histórica para o estudo da administração, através destas reformas sucessivas, de sociologia de construção do Estado e de sociologia de acção pública, o trabalho defende a ideia de que a reforma da administração, nomeadamente a descentralizadora, ao permitir uma modificação das formas de articulação entre administração e cidadãos, participa na recomposição do Estado. Com efeito a observação empírica do funcionamento quotidiano dos municípios permite percebê-los como novas arenas de difusão e de aprendizagem entre Estado e administrados. Trata-se de um processo que deve resituar- se forçosamente na intersecção dos desafios específicos dos lugares de implementação e dos quadros subjacentes às reformas. 517 $aRenegociar a Centralidade do Estado em Moçambique 606 $aPolitical Science 606 $aArea Studies 606 $acolonial administration 606 $apublic administration 606 $astate 606 $aFrelimo 606 $aMozambique 606 $acentralisation 606 $aMoçambique 606 $aadministração colonial 606 $aEstado 606 $acentralização 610 $acolonial administration 610 $apublic administration 610 $astate 610 $aFrelimo 610 $aMozambique 610 $acentralisation 615 4$aPolitical Science 615 4$aArea Studies 615 4$acolonial administration 615 4$apublic administration 615 4$astate 615 4$aFrelimo 615 4$aMozambique 615 4$acentralisation 615 4$aMoçambique 615 4$aadministração colonial 615 4$aEstado 615 4$acentralização 700 $aGuambe$b Egídio$01325845 701 $aMacuane$b José Jaime$01325846 801 0$bFR-FrMaCLE 906 $aBOOK 912 $a9910576798703321 996 $aRenegociar a Centralidade do Estado em Moçambique$93037063 997 $aUNINA LEADER 01391nam 2200409Ka 450 001 9910691786503321 005 20020718122929.0 035 $a(CKB)5470000002347525 035 $a(OCoLC)50193503 035 9 $aocm50193503 035 $a(OCoLC)995470000002347525 035 $a(EXLCZ)995470000002347525 100 $a20020718d2001 ua 0 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCombat operations C³I$b[electronic resource] $efundamentals and interactions /$fby George E. Orr 210 1$aMaxwell Air Force Base, Ala. :$cAirpower Research Institute :$cAir University Press,$d[1983 i.e. 2001] 225 1 $aResearch report ;$vno. AU-ARI-82-5 300 $a"July 1983." 300 $a"Second printing August 2001"--P. ii. 300 $aTitle from title screen. 517 $aCombat operations C³I 606 $aCommand and control systems$zUnited States 606 $aMilitary intelligence$zUnited States 615 0$aCommand and control systems 615 0$aMilitary intelligence 700 $aOrr$b George E$01384593 712 02$aAir University (U.S.).$bAirpower Research Institute. 712 02$aAir University (U.S.).$bPress. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910691786503321 996 $aCombat operations C³I$93431119 997 $aUNINA