LEADER 01009cam--2200349---450- 001 990005860720203316 005 20130704141312.0 035 $a000586072 035 $aUSA01000586072 035 $a(ALEPH)000586072USA01 035 $a000586072 100 $a20130620d1910----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aQuestioni religiose del giorno$fGeremia Bonomelli 210 $aRoma$cDesclée$d1910 215 $a229 p.$d18 cm 606 0 $aReligione$2BNCF 676 $a261 700 1$aBONOMELLI,$bGeremia$0179396 801 0$aIT$bsalbc$gISBD 912 $a990005860720203316 951 $aXV.2.A. 1470$b3152 F.C.$cXV.2.A.$d00293361 959 $aBK 969 $aCUOMO 979 $aAMENDOLA$b90$c20130620$lUSA01$h1053 979 $aAMENDOLA$b90$c20130620$lUSA01$h1055 979 $aCHIARA$b90$c20130621$lUSA01$h1152 979 $aAMENDOLA$b90$c20130704$lUSA01$h1413 996 $aQuestioni religiose del giorno$91086472 997 $aUNISA LEADER 05549nam 22006855 450 001 996466318603316 005 20200630165543.0 010 $a3-030-32281-5 024 7 $a10.1007/978-3-030-32281-6 035 $a(CKB)4100000009522969 035 $a(DE-He213)978-3-030-32281-6 035 $a(MiAaPQ)EBC5940981 035 $a(PPN)248601636 035 $a(EXLCZ)994100000009522969 100 $a20191010d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPredictive Intelligence in Medicine$b[electronic resource] $eSecond International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings /$fedited by Islem Rekik, Ehsan Adeli, Sang Hyun Park 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XIII, 178 p. 58 illus., 48 illus. in color.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v11843 311 $a3-030-32280-7 327 $aTADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data -- Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study -- Adaptive Neuro-Fuzzy Inference System-based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-state fMRI -- Deep Learning via Fused Bidirectional Attention Stacked Long Short-term Memory for Obsessive-Compulsive Disorder Diagnosis and Risk Screening -- Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning -- Predicting Response to the Antidepressant Bupropion using Pretreatment fMRI -- Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI using Bidirectionally Supervised Sample Selection -- Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer using a Non-Proportional Hazards Model -- 7 years of Developing Seed Techniques for Alzheimer's Disease Diagnosis using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis -- Generative Adversarial Irregularity Detection in Mammography Images -- Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification From a Source Graph -- Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-Resolution Neighborhoods -- Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks -- Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment -- Diagnosis of Parkinsons Disease in Genetic Cohort Patients via Stage-wise Hierarchical Deep Polynomial Ensemble learning -- Automatic Detection of Bowel Disease with Residual Networks -- Support Vector based Autoregressive Mixed Models of Longitudinal Brain Changes and Corresponding Genetics in Alzheimers Disease -- Treatment Response Prediction of Hepatocellular Carcinoma Patients from Abdominal CT Images with Deep Convolutional Neural Networks. 330 $aThis book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 18 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. . 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v11843 606 $aArtificial intelligence 606 $aMathematical statistics 606 $aOptical data processing 606 $aAlgorithms 606 $aData mining 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aArtificial intelligence. 615 0$aMathematical statistics. 615 0$aOptical data processing. 615 0$aAlgorithms. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aProbability and Statistics in Computer Science. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aData Mining and Knowledge Discovery. 676 $a610.28563 702 $aRekik$b Islem$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAdeli$b Ehsan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPark$b Sang Hyun$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466318603316 996 $aPredictive intelligence in medicine$92227350 997 $aUNISA LEADER 03527oam 2200589zu 450 001 9910791021503321 005 20230912131018.0 010 $a1-62656-393-4 035 $a(CKB)2550000001320165 035 $a(SSID)ssj0001268163 035 $a(PQKBManifestationID)11976890 035 $a(PQKBTitleCode)TC0001268163 035 $a(PQKBWorkID)11266681 035 $a(PQKB)11375031 035 $a(CaSebORM)9781576753613 035 $a(MiAaPQ)EBC1715985 035 $a(MiAaPQ)EBC6957004 035 $a(MiAaPQ)EBC7235598 035 $a(EXLCZ)992550000001320165 100 $a20160829d2006 uy 101 0 $aeng 135 $aurcn| ||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCapitalism 3.0 : a guide to reclaiming the commons 205 $a1st edition 210 31$a[Place of publication not identified]$cBerrett Koehler$d2006 215 $a1 online resource (216 pages) 225 0 $aA BK currents book Capitalism 3.0 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-57675-361-1 311 $a1-306-88967-7 327 $aTime to upgrade -- A short history of capitalism -- The limits of government -- The limits of privatization -- Reinventing the commons -- Trusteeship of creation -- Universal birth rights -- Sharing culture -- Building the commons sector -- What you can do. 330 $aThe commons ? those creations of nature and society we inherit together and must preserve for our children ? is under siege. Our current version of capitalism ? the corporate, globalized version 2.0 ? is rapidly squandering this heritage. Now, Peter Barnes offers a solution: protect the commons by giving it property rights and strong institutional managers. Barnes shows how capitalism ? like a computer ? is run by an operating system. Our current operating system gives too much power to profit-maximizing corporations that devour the commons and distribute most of their profits to a sliver of the population. And government ? which in theory should defend the commons ? is all too often a tool of those very corporations. Barnes proposes a revised operating system ? Capitalism 3.0 ? that protects the commons while preserving the many strengths of capitalism as we know it. His major innovation is the commons trust, a market based legal entity with the power to limit the use of scare commons, charge rent, and pay dividends ? in both cash and services ? to everyone. In Barnes' vision, an array of commons trusts would institutionalize our obligations to future generations, fellow citizens, and nature. Once established, they'd use markets and property rights to create a better world for us all. Capitalism 3.0 offers a practical alternative to our current flawed economic system. It points the way to a future in which we can retain capitalism's virtues while mitigating its vices. 606 $aCommons$zUnited States 606 $aPrivatization$zUnited States 606 $aCapitalism$zUnited States 606 $aBusiness & Economics$2HILCC 606 $aReal Estate, Housing & Land Use$2HILCC 615 0$aCommons 615 0$aPrivatization 615 0$aCapitalism 615 7$aBusiness & Economics 615 7$aReal Estate, Housing & Land Use 676 $a333.2 700 $aBarnes$b Peter$0163490 801 0$bPQKB 906 $aBOOK 912 $a9910791021503321 996 $aCapitalism 3.0 : a guide to reclaiming the commons$93826291 997 $aUNINA