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[null,"1.","Record Nr.",null,"UNINA990005884960403321"]
[null,null,"Autore",null,"Guerra Medici, Maria teresa"]
[null,null,"Titolo",null,"L'aria di città : donne e diritti nella città medievale / Maria Teresa Guerra Medici"]
[null,null,"Pubbl/distr/stampa",null,"Napoli : Edizioni Scientifiche Italiane, 1996"]
[null,null,"ISBN",null,"88-8114-317-8"]
[null,null,"Descrizione fisica",null,"218 p. ; 24 cm"]
[null,null,"Disciplina",null,"346.450134"]
[null,null,"Locazione",null,"FSPBC"]
[{"$nulls":4},"FLFBC"]
[{"$nulls":4},"DFD"]
[{"$nulls":4},"FGBC"]
[null,null,"Collocazione",null,"XII E 24"]
[{"$nulls":4},"346.45 GUE 1"]
[{"$nulls":4},"XI ES G 21"]
[{"$nulls":4},"VIII C 359"]
[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,"UNISA996500063103316"]
[null,null,"Titolo",null,"Artificial intelligence over infrared images for medical applications and medical image assisted biomarker discovery : first MICCAI workshop, AIIIMA 2022, and first MICCAI workshop, MIABID 2022, held in conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, proceedings / / Siva Teja Kakileti [and nine others] (editors)"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-19660-0"]
[null,null,"Descrizione fisica",null,"1 online resource (200 pages)"]
[null,null,"Collana",null,"Lecture notes in computer science ; ; Volume 13602"]
[null,null,"Disciplina",null,"610.28563"]
[null,null,"Soggetti",null,"Artificial intelligence - Medical applications"]
[{"$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,"Nota di contenuto",null,"Intro -- Preface AIIIMA 2022 -- Preface MIABID 2022 -- Organization -- Contents -- Artificial Intelligence over Infrared Images for Medical Applications -- Thermal Radiomics for Improving the Interpretability of Breast Cancer Detection from Thermal Images -- 1 Introduction -- 2 Methodology -- 2.1 Thermal Radiomics -- 2.2 Classification -- 3 Experimentation and Results -- 4 Conclusions -- References -- Radiomics for Breast IR-Imaging Classification -- 1 Introduction -- 2 Breast IR Classification in the Literature -- 3 Dataset Description -- 4 Region of Interest Segmentation -- 5 Radiomic Feature Extraction -- 6 Classification Methodology -- 7 Experiments and Results -- 8 Conclusion -- References -- Early Thermographic Screening of Breast Abnormality in Women with Dense Breast by Thermal, Fractal, and Statistical Analysis -- 1 Background -- 2 Methods -- 3 Results -- 3.1 Thermal Feature-Based Analysis -- 3.2 Fractal Feature-Based Analysis -- 3.3 Statistical Feature-Based Analysis -- 4 Discussion -- 5 Conclusion and Futurescope -- References -- A Novel Thermography-Based Artificial Intelligence-Powered Solution for Screening Breast Cancer -- 1 Introduction -- 1.1 Thermography -- 1.2 Related Work -- 1.3 AI-Powered Breast Cancer Prediction Tool by AI Talos -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 CNN Methodology -- 3 Experimental Results -- 4 Conclusion -- References -- Thermographic Toothache Screening by Artificial Intelligence -- 1 Introduction, Review "]
[{"$nulls":4},"and Objectives -- 2 Materials and Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Non-fever COVID-19 Detection by Infrared Imaging -- 1 Introduction -- 2 Materials and Methods -- 2.1 Infrared Camera Calibration and Precision Assessment -- 2.2 Standard Data Bank Construction (Phase 1) -- 2.3 Classification Algorithm -- 2.4 Prospective Study (Phase 2)."]
[{"$nulls":4},"2.5 Statistical Analysis -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Automated Thermal Screening for COVID-19 Using Machine Learning -- 1 Introduction -- 2 Dataset -- 2.1 Thermal Surveillance Dataset -- 2.2 Augmented Surveillance Dataset -- 2.3 Lighting Dataset -- 3 Methodology -- 3.1 Image Preprocessing -- 3.2 Face Detection -- 3.3 Fever Detection -- 3.4 Mask Classification -- 4 Experiments and Results -- 4.1 Face Detection -- 4.2 Mask Classification -- 5 Conclusion -- References -- An Automated Approach for Screening COVID-19 from Thermal Images Using Convolutional Neural Network -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Overview -- 3.2 YOLOv5 as Mask Detection Module -- 3.3 Fever Detection Module -- 4 Results and Discussion -- 5 Conclusion -- References -- Infrared Technology for Vascular Abnormality in Finding of Abdominal Aortic Aneurysm -- 1 Introduction -- 1.1 Objective -- 2 Methodology -- 2.1 Model Setup -- 2.2 Boundary Conditions -- 2.3 Physical and Thermal Properties -- 3 Verification Studies for FSI Analysis -- 4 Result and Discussions -- 4.1 Transient FSI Analysis -- 5 Limitations -- 6 Conclusion -- References -- Non-invasive Thermal Imaging for Estimation of the Fecundity of Live Female Onchocerca Worms -- 1 Introduction -- 2 Dataset Description -- 2.1 Study Site and Population -- 2.2 Imaging Protocol -- 2.3 Histopathology and Ground truth -- 3 Methodology -- 3.1 Data Pre-processing -- 3.2 Feature Extraction -- 3.3 Classification -- 4 Experiments and Results -- 5 Conclusion -- References -- Medical Image Assisted Biomarker Discovery -- Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers -- 1 Introduction -- 2 Methods -- 3 Experiments and Results -- 3.1 Dataset and Implementation Details -- 3.2 Evaluating Counterfactuals and Discovered Image-Based Markers."]
[{"$nulls":4},"3.3 Counterfactual Results -- 4 Conclusions -- References -- CoRe: An Automated Pipeline for the Prediction of Liver Resection Complexity from Preoperative CT Scans -- 1 Introduction -- 2 Methods -- 2.1 Liver, Lesion, and Vessel Segmentation -- 2.2 Topological Analysis of the Liver Vasculature -- 2.3 Quantitative Imaging Biomarkers for LR Complexity Prediction -- 3 Experiments -- 3.1 Datasets and Preprocessing -- 3.2 Training, Evaluation, and Inference -- 4 Results -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 5 Discussion and Conclusion -- References -- Diffusion Tensor Imaging Biomarkers for Parkinson's Disease Symptomatology -- 1 Introduction -- 1.1 Voxel-Based Diffusion Analysis and Voxel-Based Diktiometry -- 2 Materials and Methods -- 2.1 Patient Images and Clinical Scores -- 2.2 Preprocessing -- 2.3 Convolutional Neural Network -- 2.4 Diffusion Measures, Sensitivity Maps, and Statistical Processing -- 3 Results and Discussion -- 4 Conclusion -- References -- Prediction of Immune and Stromal Cell Population Abundance from Hepatocellular Carcinoma Whole Slide Images Using Weakly Supervised Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Gene Expression Processing -- 2.3 Image Preprocessing -- 2.4 Deep Learning Models -- 2.5 Attention Map Generation and Statistical Analysis -- 2.6 Inflammatory Cell Density Map Generation -- 3 Results -- 3.1 Unsupervised Hierarchical Clustering of Samples -- 3.2 Evaluation of Deep Learning Models for the Prediction of Activation "]
[{"$nulls":4},"of Cell Populations -- 3.3 Interpretability and Relationships with Immunotherapy-Related Gene Signatures and with Inflammatory Cells -- 4 Discussion and Conclusion -- References -- Enhancing Local Context of Histology Features in Vision Transformers -- 1 Introduction -- 2 Methods -- 3 Experiments -- 4 Conclusion -- References."]
[{"$nulls":4},"DCIS AI-TIL: Ductal Carcinoma In Situ Tumour Infiltrating Lymphocyte Scoring Using Artificial Intelligence -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Cell Detection, Cell Classification and Hotspot Analysis -- 3.2 DCIS Segmentation Using GAN -- 3.3 Stromal TIL Scoring Using Artificial Intelligence -- 3.4 Statistical Analysis -- 4 Results and Discussion -- References -- Predictive Biomarkers in Melanoma: Detection of BRAF Mutation Using Dermoscopy -- 1 Introduction -- 2 Methodology -- 2.1 Pre-training Phase -- 2.2 BRAF Classification -- 3 Experimental Setup -- 3.1 Dataset and Evaluation Metrics -- 3.2 Experimental Challenges -- 3.3 Network Training and Computational Environment -- 4 Results and Discussion -- 5 Conclusion -- References -- Author Index."]
[null,"3.","Record Nr.",null,"UNISALENTO991000255929707536"]
[null,null,"Autore",null,"Segal, Ronald"]
[null,null,"Titolo",null,"La guerra delle razze / Ronald Segal"]
[null,null,"Pubbl/distr/stampa",null,"Milano : Mursia, c1968"]
[null,null,"Descrizione fisica",null,"409 p. ; 22 cm."]
[null,null,"Collana",null,"Tempo d'oggi ; 1"]
[null,null,"Disciplina",null,"301.45"]
[null,null,"Soggetti",null,"Razzismo"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Tit. orig.: The race war"]