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[null,"1.","Record Nr.",null,"UNICAMPANIASUN0010580"]
[null,null,"Autore",null,"Carnelutti, Francesco"]
[null,null,"Titolo",null,"1: Funzione e composizione del processo / Francesco Carnelutti"]
[null,null,"Pubbl/distr/stampa",null,"VIII, 984 p. ; 24 cm"]
[null,null,"Edizione",null,"[Padova : Cedam]"]
[null,null,"Descrizione fisica",null,"Volume presente anche nel fondo Raffaele Papa e nel  Fondo Salvatore Biggiero."]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNISA996495570803316"]
[null,null,"Titolo",null,"Interpretability of machine intelligence in medical image computing : 5th international workshop, iMIMIC 2022, held in conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, proceedings / / edited by Mauricio Reyes, Pedro Henriques Abreu, and Jaime Cardoso"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-17976-5"]
[null,null,"Descrizione fisica",null,"1 online resource (134 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; v.13611"]
[null,null,"Disciplina",null,"616.0754"]
[null,null,"Soggetti",null,"Computer-assisted surgery"]
[{"$nulls":4},"Diagnostic imaging - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Interpretable Lung Cancer Diagnosis with Nodule Attribute Guidance and Online Model Debugging -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Collaborative Model Architecture with Attribute-Guidance -- 3.2 Debugging Model with Semantic Interpretation -- 3.3 Explanation by Attribute-Based Nodule Retrieval -- 4 Experiments and Results -- 4.1 Implementation -- 4.2 Quantitative Evaluation -- 4.3 Trustworthiness Check and Interpretable Diagnosis -- 5 Conclusions -- References -- Do Pre-processing and Augmentation Help Explainability? A Multi-seed Analysis for Brain Age Estimation -- 1 Introduction -- 2 Related Work -- 3 Methods -- 4 Results -- 4.1 Performance -- 4.2 Voxel Agreement -- 4.3 Atlas-Based Analyses -- 4.4 Region Validation -- 5 Conclusion -- References -- Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Architecture -- 3.2 Preprocessing -- 3.3 Loss Function -- 3.4 Data Augmentation -- 4 Experiments -- 4.1 Data -- 4.2 Results -- 5 Conclusion -- References -- Reducing Annotation Need in Self-explanatory Models for Lung Nodule Diagnosis -- 1 Introduction -- 2 Method -- 3 Experimental Results -- 3.1 Prediction Performance of Nodule Attributes and Malignancy -- 3.2 Analysis of Extracted Features in Learned Space -- 3.3 Ablation Study -- 4 Conclusion -- References -- Attention-Based Interpretable Regression "]
[{"$nulls":4},"of Gene Expression in Histology -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Multiple Instance Regression of Gene Expression -- 2.3 Attention-Based Model Interpretability -- 2.4 Evaluation of Performance and Interpretability -- 3 Experiments and Results -- 3.1 Network Training -- 3.2 Quantitative Model Evaluation -- 3.3 Attention-Based Identification of Hotspots and Patterns."]
[{"$nulls":4},"3.4 Quantitative Evaluation of the Attention -- 4 Discussion -- 5 Conclusion -- A Description of Selected Genes -- B Detailed Model Evaluation -- C Additional Visualizations -- D Single-Cell Co-expression -- References -- Beyond Voxel Prediction Uncertainty: Identifying Brain Lesions You Can Trust -- 1 Introduction -- 2 Our Framework: Graph Modelization for Lesion Uncertainty Quantification -- 2.1 Monte Carlo Dropout Model and Voxel-Wise Uncertainty -- 2.2 Graph Dataset Generation -- 2.3 GCNN Architecture and Training -- 3 Material and Method -- 3.1 Data -- 3.2 Comparison with Known Approaches -- 3.3 Evaluation Setting -- 3.4 Implementation Details -- 4 Results and Discussion -- 5 Conclusion -- References -- Interpretable Vertebral Fracture Diagnosis -- 1 Introduction -- 1.1 Related Work -- 2 Methodology -- 2.1 Vertebral Fracture Detection -- 2.2 Semantic Concept Extraction (Correlation) -- 2.3 Visualization of Highly Correlating Concepts at Inference -- 3 Experimental Setup -- 4 Results and Discussion -- 4.1 Clinical Meaningfulness of Extracted Semantic Concepts -- 4.2 Single-Inference Concept Visualization -- 5 Conclusion -- References -- Multi-modal Volumetric Concept Activation to Explain Detection and Classification of Metastatic Prostate Cancer on PSMA-PET/CT -- 1 Introduction -- 2 Data -- 3 Method -- 3.1 Preprocessing -- 3.2 Detection -- 3.3 Classification -- 3.4 Explainable AI -- 4 Results -- 4.1 Detection -- 4.2 Classification -- 4.3 Explainable AI -- 5 Discussion -- 6 Conclusion -- References -- KAM - A Kernel Attention Module for Emotion Classification with EEG Data -- 1 Introduction -- 2 Related Work -- 3 Kernel Attention Module -- 4 Experiments -- 5 Conclusion -- References -- Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful -- 1 Introduction -- 2 Related Work -- 2.1 XAI in Medicine."]
[{"$nulls":4},"3 Model Setup -- 3.1 Data Pre-Processing -- 3.2 Model Architecture -- 4 Explanations -- 4.1 LIME -- 4.2 RISE -- 4.3 SHAP -- 5 Evaluating Explanations -- 5.1 One-Way ANOVA -- 5.2 Kendall's Tau -- 5.3 Radiologist Evaluation -- 5.4 Threats to Validity -- 6 Observations and Discussion -- 6.1 Discussion -- A Appendix -- A.1 Model Training Results -- A.2 Choosing L Parameter for LIME -- A.3 One-Way ANOVA Results -- A.4 Pixel Agreement Statistics -- A.5 Ranked Biased Overlap (RBO) Results -- A.6 Kendall's Tau Results -- A.7 Radiologist Opinions -- A.8 Explanation Examples -- References -- Author Index."]
[null,"3.","Record Nr.",null,"UNINA9910788149503321"]
[null,null,"Titolo",null,"The Marion Experiment : long-term solitary confinement and the supermax movement / / edited by Stephen C. Richards"]
[null,null,"Pubbl/distr/stampa",null,"Carbondale, Illinois : , : Southern Illinois University Press, , [2015]"]
[{"$nulls":4},"©2015"]
[null,null,"ISBN",null,"0-8093-3377-5"]
[null,null,"Descrizione fisica",null,"1 online resource (621 p.)"]
[null,null,"Collana",null,"Elmer h johnson & carol holmes johnson series in criminology"]
[null,null,"Classificazione",null,"SOC004000SOC030000"]
[null,null,"Disciplina",null,"365/.33"]
[null,null,"Soggetti",null,"Prisons - Law and legislation - United States"]
[{"$nulls":4},"Imprisonment - United States"]
[{"$nulls":4},"Solitary confinement - United States"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Cover Page; Title Page; Copyright Page; Contents; Foreword: The Phenomenon of USP Marion; Preface; Acknowledgments; Introduction; Part One. Convict Experience With Solitary Confinement; 1. The Politicization of the Hole in Indiana and Missouri; 2. The Realities of Special Housing Units in the Federal Bureau of Prisons; 3. Going to the Hole in California: Cauldron of Solitude; 4. The Boy Scout in Solitary at USP Lompoc; 5. Long-Term Solitary Segregation in the United States and Canada; Part Two. The Effects of Solitary Confinement; 6. Theorizing \"Marionization\" and the Supermax Prison Movement"]
[{"$nulls":4},"7. Female Prisoners and Solitary Confinement 8. The Scene of the Crime: Children in Solitary Confinement; 9. Colorado Supermax Study: What the Critics Say and the Future Holds; 10. Revisiting the Mental Health Effects of Solitary Confinement on Prisoners in Supermax Units: A Psychological Jurisprudence Perspective; Part Three. International Perspectives on Solitary Confinement; 11. Doing Hard Time in the United Kingdom; 12. Solitary Confinement and Convict Segregation in French Prisons; 13. Israeli Maximum-Security Prisons; Conclusion: Rethinking Prisons in the 21st Century; References"]
[{"$nulls":4},"Contributors Index; Back Cover"]
[null,null,null,"Sommario/riassunto","\"The Marion Experiment combines academic research with personal accounts by prisoners to investigate solitary confinement and supermax prisons. USP Marion became a model for supermax prisons, with many other prison systems--in the U.S. and abroad--copying the "]
[{"$nulls":4},"special architectural and program innovations there\"--"]