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AI for disease surveillance and pandemic intelligence : intelligent disease detection in action / / Arash Shaban-Nejad, Martin Michalowski, Simone Bianco, editors
| AI for disease surveillance and pandemic intelligence : intelligent disease detection in action / / Arash Shaban-Nejad, Martin Michalowski, Simone Bianco, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] |
| Descrizione fisica | 1 online resource (335 pages) |
| Disciplina | 610.28563 |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Artificial intelligence - Medical applications
Public health surveillance Artificial intelligence |
| ISBN | 3-030-93080-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910552722303321 |
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence for Personalized Medicine [[electronic resource] ] : Promoting Healthy Living and Longevity / / edited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco
| Artificial Intelligence for Personalized Medicine [[electronic resource] ] : Promoting Healthy Living and Longevity / / edited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco |
| Autore | Shaban-Nejad Arash |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (306 pages) |
| Disciplina | 610.28563 |
| Altri autori (Persone) |
MichalowskiMartin
BiancoSimone |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Biomedical engineering Engineering - Data processing Artificial intelligence Computational Intelligence Biomedical Engineering and Bioengineering Data Engineering Artificial Intelligence |
| ISBN | 3-031-36938-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Contributors -- Abbreviations -- Artificial Intelligence for Personalized Care, Wellness, and Longevity Research -- 1 Introduction -- 2 The Role of AI and Data Science in Ageing and Longevity Research -- 3 Advances in AI Technologies and Data Analytics in Healthcare -- References -- Towards Trust of Explainable AI in Thyroid Nodule Diagnosis -- 1 Introduction -- 1.1 Dataset -- 2 Related Work -- 2.1 Backpropagation-Based Methods -- 2.2 CAM-Based Methods -- 2.3 Perturbation-Based Methods -- 2.4 Statistic-Based Methods -- 2.5 XAI in the Medical Diagnosis System -- 3 Methodology -- 3.1 Object Detector and XAI Categorization -- 3.2 XAI Methods for the Localization Task -- 4 Results -- 4.1 Qualitative Evaluation -- 4.2 Quantitative Evaluation -- 5 Conclusion -- References -- Federated Learning over Harmonized Data Silos -- 1 Introduction -- 2 Background -- 3 Federated Learning and Integration -- 3.1 Federated Learning Programming Model -- 3.2 Data Harmonization and Imputation -- 4 Discussion -- References -- Investigation of Drift Detection for Clinical Text Classification -- 1 Introduction -- 2 Two-Sample Statistical Hypothesis Testing -- 2.1 Kernel Maximum Mean Discrepancy -- 2.2 Kolmogorov-Smirnov Test -- 3 The Clinical Case Study -- 3.1 The Drift Monitoring Schema -- 3.2 Drift Data Setup -- 3.3 Sub-sampling -- 4 Analysis -- 4.1 Analysis with Different Drift Ratios -- 4.2 Analysis of Time Performance -- 4.3 Discussion -- 5 Conclusion and Future Work -- References -- Neural Bandits for Data Mining: Searching for Dangerous Polypharmacy -- 1 Introduction -- 2 Problem Formulation -- 3 Proposed Approach -- 3.1 Neural Contextual Bandits -- 3.2 Generating Relevant Available Action Sets -- 3.3 OptimNeuralTS -- 4 Experiments -- 4.1 Synthetic Data Generation -- 4.2 Experimental Setup -- 5 Results -- 5.1 Impact of Ensemble.
5.2 Generalization -- 6 Related Work -- 7 Conclusion -- References -- Dynamic Outcomes-Based Clustering of Disease Trajectory in Mechanically Ventilated Patients -- 1 Introduction and Related Work -- 2 Methods -- 3 Data -- 4 Prediction Tasks -- 5 Results -- 6 Discussion -- 7 Limitations and Future Work -- 8 Summary -- References -- Bayesian-Based Parameter Estimation to Quantify Trust in Medical Devices -- 1 Introduction -- 2 Parameter Estimation of Bayesian Network -- 2.1 Data-Oriented Bayesian Parameter Estimation -- 2.2 Constructing the Trust Network -- 3 Experimental Evaluation -- 3.1 Parameter Estimation -- 3.2 Results and Discussion -- 4 Conclusion and Future Work -- References -- EEG Analysis of Neurodevelopmental Disorders by Integrating Wavelet Transform and Visual Analysis -- 1 Introduction -- 2 Previous Work -- 3 Methods -- 3.1 Data Description -- 3.2 Proposed Approach -- 3.3 Channel-Based Predictive Model Generation -- 3.4 Visual Analysis -- 4 Results -- 5 Conclusions and Future Works -- References -- Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN -- 1 Introduction -- 2 Background and Related Work -- 2.1 Algorithmic Auditing in ML for Healthcare -- 2.2 Measuring Health Equity Barriers -- 2.3 Fairness and Local Bias Detection -- 3 Methodology -- 3.1 Clinical NLP Pretrained Embeddings -- 3.2 Automatic Bias Detection -- 4 Data and Setup -- 5 Results -- 5.1 Aggregate Analysis -- 5.2 Case Study: Diabetes Mellitus -- 6 Discussion -- 6.1 Ethical Statement and Limitations -- References -- Identification, Explanation and Clinical Evaluation of Hospital Patient Subtypes -- 1 Introduction -- 2 Method -- 2.1 Data Source and Conditions -- 2.2 Dimensionality Reduction and Clustering -- 2.3 Clustering Explanations -- 2.4 Clinical Evaluation -- 3 Results -- 3.1 Cluster Characterization. 3.2 Cluster Visualisation and Vitals -- 3.3 ICD10 Codes -- 3.4 Surrogate Explanations -- 3.5 Clinical Interpretation of Clusters -- 4 Discussion and Conclusion -- References -- Automatically Extracting Information in Medical Dialogue: Expert System and Attention for Labelling -- 1 Introduction -- 2 Related Work -- 2.1 Medical Dialogue Information Extraction -- 2.2 Mixture of Experts -- 3 Approach -- 3.1 Embedding layer -- 3.2 Expert information extraction layer -- 3.3 Self-Attention Labeling Layer -- 3.4 Output Layer -- 3.5 Loss Function -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Evaluation Metrics -- 4.3 Main Results -- 4.4 Case Analysis -- 4.5 Conclusion -- References -- Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer's Disease -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Selection of the Most Informative Training Dataset -- 3.2 Feature Extraction -- 3.3 Class Decomposition -- 3.4 Classification and Class Composition -- 4 Results and Discussion -- 4.1 Expierments Setup -- 4.2 Classification and Class Composition -- 4.3 Comparison with Existing Methods -- 5 Conclusion -- References -- Knowledge Augmentation for Early Depression Detection -- 1 Introduction -- 2 Related Work -- 3 Research Questions -- 4 Method: Soft Thresholding for Boundary Region Users (STBound) -- 4.1 Hard Threshold Line -- 4.2 Soft Threshold Line -- 4.3 Boundary Region -- 4.4 System Architecture -- 5 Analysis of Proposed Model -- 6 Experimentation -- 6.1 Datasets -- 6.2 Ethics and Privacy -- 6.3 Experimental Setup -- 6.4 Language Study -- 7 Results and Analysis -- 8 Bipolar Verses Depressed -- 9 Conclusion -- References -- Deep Annotation of Therapeutic Working Alliance in Psychotherapy -- 1 Introduction -- 2 Problem Setting -- 2.1 Working Alliance Analysis -- 2.2 Psychotherapy Transcript Dataset -- 3 Methods. 3.1 Working Alliance Inventories -- 3.2 Sentence Embeddings -- 4 Results -- 4.1 Insights from Analyzing Psychotherapy Transcripts -- 5 Discussion -- 6 Ethical Statements -- 7 Conclusions -- 8 Reproducibility Statement -- References -- Neural Topic Modeling of Psychotherapy Sessions -- 1 Introduction -- 2 Related Work on Topic Modeling -- 3 Therapy Topic Modeling Framework -- 4 Results -- 4.1 Evaluation Metrics -- 4.2 Quantitative Evaluations of the Topic Models -- 4.3 Temporal Dynamics of the Topic Models -- 4.4 Interpretable Insights from the Learned Topics -- 4.5 Ranked Topics Informed by Working Alliance -- 5 Conclusions -- References -- BAUFER: A Baseline-Enabled Facial Expression Recognition Pipeline Trained with Limited Annotations -- 1 Introduction -- 1.1 Baseline Calibration -- 1.2 Action Units for Granular Analysis and Interpretability -- 1.3 Scarcity of Training Data -- 2 Related Work -- 2.1 Facial Data Annotation -- 2.2 Facial Recognition for Identification -- 2.3 Categorical Emotion Annotation -- 2.4 Annotations Produced with FACS -- 2.5 Deep Learning Models -- 3 Methodology -- 3.1 BAUFER Pipeline Overview -- 3.2 AU Classification -- 3.3 Baseline Implementation -- 3.4 Multi-stage Training -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Experiments -- 4.3 Evaluation and Ablation Study -- 4.4 Multi-stage Training -- 4.5 Baseline Versus No Baseline -- 4.6 Performance of BAUFER -- 5 Discussion -- 6 Conclusion -- References -- Robustness for ECG Classification by Adversarial Training Over Clinical Features -- 1 Introduction -- 2 Background and Preliminaries -- 2.1 Low and High Level Clinical Features -- 2.2 Adversarial Attacks -- 3 Proposed Methodology -- 3.1 Low Level Perturbations -- 3.2 High Level Perturbations -- 3.3 Adversarial Training Against Perturbations -- 4 Experiments -- 4.1 Adversarial Training Against Low Level Perturbations. 4.2 Adversarial Training Against High and Low Level Perturbations -- 4.3 Evaluating Robustness to Low Level Perturbations -- 4.4 Evaluating Sensitivity to High Level Perturbations -- 5 Related Work -- 6 Conclusions and Future Work -- References -- A Transformer-Based Deep Learning Algorithm to Auto-Record Undocumented Clinical One-Lung Ventilation Events -- 1 Introduction -- 2 Related Works -- 3 Data Management -- 4 Method -- 4.1 Problem Definition -- 4.2 Variable Embeddings -- 4.3 Transformer Blocks for Temporal Learning -- 4.4 Frequency Domain Features -- 4.5 Label Smoothing -- 4.6 Loss Function -- 5 Results -- 5.1 Model Performance -- 5.2 Feature Importance Decomposition -- 6 Discussion and Limitation -- References -- Analyzing the Trends of Responses to COVID-19 Related Tweets from News Stations: An Analysis of Three Countries -- 1 Introduction -- 2 Related Works -- 2.1 COVID-19 Pandemic -- 2.2 Political Campaigns -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Prerequisites -- 4 Results -- 4.1 RQ1: Which COVID-19 Related Topics from Different News Stations Were the Most Popular Overall? -- 4.2 RQ2: Is There a Difference in the Responses to COVID-19 Related Tweets from Different News Stations? -- 4.3 RQ3: Do Differences in the Responses to COVID-19 Related Tweets Occur Between News Stations with Different Political Stances? -- 5 Discussion and Future Work -- 6 Conclusion -- References -- Understanding the Role of Questions in Mental Health Support-Seeking Forums -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 3.1 Annotation -- 4 Features -- 5 Experiments and Results -- 6 Conclusion and Future Work -- 7 Limitations -- 8 Ethics -- References. |
| Record Nr. | UNINA-9910743687803321 |
Shaban-Nejad Arash
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational Color Imaging [[electronic resource] ] : 6th International Workshop, CCIW 2017, Milan, Italy, March 29-31, 2017, Proceedings / / edited by Simone Bianco, Raimondo Schettini, Alain Trémeau, Shoji Tominaga
| Computational Color Imaging [[electronic resource] ] : 6th International Workshop, CCIW 2017, Milan, Italy, March 29-31, 2017, Proceedings / / edited by Simone Bianco, Raimondo Schettini, Alain Trémeau, Shoji Tominaga |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIII, 283 p. 132 illus.) |
| Disciplina | 621.367 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Computer graphics Pattern recognition Image Processing and Computer Vision Computer Graphics Pattern Recognition |
| ISBN | 3-319-56010-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Color image processing -- Color image quality -- Color in digital cultural heritage -- Spectral imaging -- Color characterization -- Color image analysis. |
| Record Nr. | UNISA-996466213703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Computational Color Imaging : 6th International Workshop, CCIW 2017, Milan, Italy, March 29-31, 2017, Proceedings / / edited by Simone Bianco, Raimondo Schettini, Alain Trémeau, Shoji Tominaga
| Computational Color Imaging : 6th International Workshop, CCIW 2017, Milan, Italy, March 29-31, 2017, Proceedings / / edited by Simone Bianco, Raimondo Schettini, Alain Trémeau, Shoji Tominaga |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIII, 283 p. 132 illus.) |
| Disciplina | 621.367 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Computer graphics Pattern recognition Image Processing and Computer Vision Computer Graphics Pattern Recognition |
| ISBN | 3-319-56010-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Color image processing -- Color image quality -- Color in digital cultural heritage -- Spectral imaging -- Color characterization -- Color image analysis. |
| Record Nr. | UNINA-9910485001803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimodal AI in healthcare : a paradigm shift in health intelligence / / Arash Shaban-Nejad, Martin Michalowski, Simone Bianco, editors
| Multimodal AI in healthcare : a paradigm shift in health intelligence / / Arash Shaban-Nejad, Martin Michalowski, Simone Bianco, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (417 pages) : illustrations |
| Disciplina | 610.285 |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Artificial intelligence - Medical applications
Medical informatics Artificial Intelligence Medical Informatics |
| Soggetto genere / forma |
Congress.
Conference papers and proceedings. |
| ISBN | 3-031-14771-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge -- Customized Training of Pretrained Language Models to Detect Post Intents in Online Health Support Groups -- EXPECT-NLP: An Integrated Pipeline and User Interface for Exploring Patient Preferences Directly from Patient-Generated Text. |
| Record Nr. | UNINA-9910632485103321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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