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[null,"1.","Record Nr.",null,"UNISA990000801110203316"]
[null,null,"Autore",null,"VENTRA, Carmelo"]
[null,null,"Titolo",null,"La scuola medica salernitana : rievocata nel salone del Comune in occasione del 30. Congresso della società di italiana di stomatologia : Salerno, 16 settembre 1955 / Carmelo Ventra ; discorso pubblicato a cura del Comune"]
[null,null,"Pubbl/distr/stampa",null,"Salerno : Sensoli & Vittori, 1955"]
[null,null,"Descrizione fisica",null,"13 p. ; 24 cm"]
[null,null,"Disciplina",null,"610.945741"]
[null,null,"Collocazione",null,"XV.1.A. Misc. 99(V G MISC.1/66)"]
[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,"UNINA9910452718203321"]
[null,null,"Titolo",null,"Cortisol [[electronic resource] ] : physiology, regulation and health implications / / Alonzo Esposito and Vito Bianchi, editors"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Nova Science Publishers, c2012"]
[null,null,"ISBN",null,"1-61942-465-7"]
[null,null,"Descrizione fisica",null,"1 online resource (176 p.)"]
[null,null,"Collana",null,"Human anatomy and physiology"]
[null,null,"Disciplina",null,"612.01577"]
[null,null,"Soggetti",null,"Hydrocortisone"]
[{"$nulls":4},"Cortisone"]
[{"$nulls":4},"Electronic books."]
[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,"\"\"CORTISOL PHYSIOLOGY, REGULATION  AND HEALTH IMPLICATIONS\"\"; \"\"CORTISOL PHYSIOLOGY, REGULATION  AND HEALTH IMPLICATIONS\"\"; \"\"CONTENTS \"\"; \"\"PREFACE \"\"; \"\"CORTISOL TRANSPORT ACROSS BIOLOGICAL BARRIERS\"\"; \"\"ABSTRACT \"\"; \"\"TRANSPORT OF CORTISOL ACROSS THE BLOOD-BRAIN BARRIER: THE CONTROVERSY ABOUT P-GLYCOPROTEIN \"\"; \"\"DEPRESSION: THERAPEUTIC STRATEGIES  RELATED TO CORTISOL\"\"; \"\"EFFECT OF CORTISOL ON THE PERMABILITY  OF BIOLOGICAL MEMBRANES \"\"; \"\"CONCLUSION \"\"; \"\"ACKNOWLEDGMENTS \"\"; \"\"REFERENCES \"\"; \"\"CORTISOL: PHYSIOLOGY, REGULATION AND HEALTH IMPLICATIONS \"\"; \"\"ABSTRACT \"\"; \"\"INTRODUCTION \"\""]
[{"$nulls":4},"\"\"What Is Cortisol?\"\"\"\"What Is Stress? \"\"; \"\"HYPOTHALAMIC-PITUITARY-ADRENAL AXIS:  IN TIMES OF STRESS AND REST \"\"; \"\"HPA Axis in Times of Stress \"\"; \"\"HPA Axis in Times of Rest \"\"; \"\"GLUCOCORTICOID RECEPTOR TYPES \"\"; \"\"Role of the Genomic MR and GR Receptors \"\"; \"\"Role of the Non-Genomic MR and GR-Like Receptors \"\"; \"\"MODES OF CORTISOL ACTION \"\"; \"\"EFFECTS OF CORTISOL ON THE BODY AND MIND \"\"; \"\"Immune System â€? Inflammatory Cytokines \"\"; \"\"Cognition - Learning and Memory \"\"; \"\"Emotion - Subjective Psychological Distress and Physiological Stress Response\"\""]
[{"$nulls":4},"\"\"Maladaptive Effects of Cortisol \"\"\"\"REGULATORY MECHANISMS \"\"; \"\"Hippocampus \"\"; \"\"Amygdala \"\"; \"\"Prefrontal Cortex \"\"; \"\"INDIVIDUAL DIFFERENCES \"\"; \"\"CONCLUSION \"\"; \"\"REFERENCES \"\"; \"\"HEIGHTENED ENDOCRINE RESPONSES TO DAILY LIFE STRESSORS IN HEALTHY WOMEN AT FAMILIAL RISK FOR BREAST CANCER \"\"; \"\"ABSTRACT \"\"; \"\"INTRODUCTION \"\"; \"\"NATURAL EXPERIMENTAL APPROACH TO  "]
[{"$nulls":4},"STUDYING STRESS IN EVERYDAY LIFE\"\"; \"\"EXPERIMENTAL DESIGN FOR THIS STUDY \"\"; \"\"ENDOCRINE MEASURES AND DATA COLLECTION PROTOCOL\"\"; \"\"Procedures\"\"; \"\"Psychological Evaluation  \"\"; \"\"REACTIVITY TO WORK STRESSORS: PRINCIPAL FINDINGS \"\""]
[{"$nulls":4},"\"\"Cortisol \"\"\"\"Epinephrine and Norepinephrine \"\"; \"\"REPRODUCIBILITY OF THE HEIGHTENED REACTIVITY RESPONSE  TO WORK STRESSORS \"\"; \"\"Cortisol \"\"; \"\"Epinephrine and Norepinephrine \"\"; \"\"PSYCHOLOGICAL FACTORS, BREAST CANCER RISK  AND CORTISOL REACTIVITY \"\"; \"\"DISCUSSION \"\"; \"\"CONCLUSION \"\"; \"\"ACKNOWLEDGMENTS \"\"; \"\"REFERENCES\"\"; \"\"BIOPSYCHOSOCIAL CORRELATES OF CORTISOL ACTIVITY IN CHILDREN EXPOSED  TO NATURAL DISASTERS \"\"; \"\"ABSTRACT\"\"; \"\"STRESS REACTIONS IN ADULTS \"\"; \"\"STRESS REACTIONS IN CHILDREN \"\"; \"\"DEVELOPMENTAL FACTORS \"\"; \"\"SOCIAL FACTORS \"\"; \"\"SEX DIFFERENCES\"\""]
[{"$nulls":4},"\"\"CASE STUDY: HURRICANE KATRINA \"\"\"\"Psychophysical Reactions \"\"; \"\"Maternal Factors \"\"; \"\"Sex Differences \"\"; \"\"Other Social Factors \"\"; \"\"IMPLICATIONS FOR FUTURE RESEARCH \"\"; \"\"CONCLUSION \"\"; \"\"REFERENCES \"\"; \"\"CORTISOL-CORTISONE SHUTTLE: A FUNCTIONAL INDICATOR OF  11Î?-HSD ACTIVITY \"\"; \"\"ABSTRACT \"\"; \"\"INTRODUCTION \"\"; \"\"1. CCR IN GLUCOCORTICOID THERAPY \"\"; \"\"2. ELEVATED FETAL CCR \"\"; \"\"3. CCR IN ACUTE PHASE RESPONSE\"\"; \"\"4. CCR IN ACUTE PULMONARY TUBERCULOSIS (PTB)\"\"; \"\"5. CCR IN SMALL GESTATIONAL AGE CHILDREN (SGA) \"\"; \"\"6. CCR IN GROWTH HORMONE (GH) REPLACEMENT THERAPY \"\""]
[{"$nulls":4},"\"\"7. CCR FOR PREDICTING CLINICAL OUTCOME OF IVF-ET  (IN VITRO FERTILIZATION AND EMBRYO TRANSFER) \"\""]
[null,"3.","Record Nr.",null,"UNISA996547951803316"]
[null,null,"Titolo",null,"Advances in non-invasive biomedical signal sensing and processing with machine learning / / edited by Saeed Mian Qaisar, Humaira Nisar, and Abdulhamit Subasi"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2023]"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-23239-9"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (385 pages)"]
[null,null,"Disciplina",null,"610.28"]
[null,null,"Soggetti",null,"Machine learning"]
[{"$nulls":4},"Medical innovations"]
[{"$nulls":4},"Biosensors"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"1. Introduction to non-invasive biomedical signals for healthcare -- 2. Signal Acquisition Preprocessing and Feature Extraction Techniques for Biomedical Signals -- 3. The Role of EEG as Neuro-Markers for Patients with Depression: A systematic Review -- 4. Brain-Computer Interface (BCI) Based on the EEG Signal Decomposition Butterfly Optimization and Machine Learning -- 5. Advances in the analysis of electrocardiogram in context of mass screening: technological trends and application of artificial intelligence anomaly detection -- 6. Application of Wavelet Decomposition and Machine Learning for the sEMG Signal based Gesture Recognition -- 7. Review of EEG Signals Classification using Machine Learning and Deep-learning Techniques -- 8. \"Biomedical signal processing and artificial intelligence in EOG signals\" -- 9. Peak Spectrogram and Convolutional Neural Network-based Segmentation and Classification for Phonocardiogram Signals -- 10. Eczema skin lesions segmentation using deep neural network (U-net) -- 11. Biomedical signal processing for automated detection of sleep arousals Based on Multi-Physiological Signals with Ensemble learning methods -- 12. Deep Learning Assisted Biofeedback -- 13. Estimations of Emotional Synchronization Indices for Brain regions using Electroencephalogram Signal Analysis -- 14. Recognition Enhancement of Dementia Patients’ Working Memory using Entropy-based Features and Local Tangent Space Alignment Algorithm."]
[null,null,null,"Sommario/riassunto","This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors’ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems."]