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Pregnancy with artificial intelligence : a 9.5 months journey from preconception to birth / / Smaranda Belciug, Dominic Iliescu
| Pregnancy with artificial intelligence : a 9.5 months journey from preconception to birth / / Smaranda Belciug, Dominic Iliescu |
| Autore | Belciug Smaranda |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (283 pages) |
| Disciplina | 610.285 |
| Collana | Intelligent systems reference library |
| Soggetto topico |
Pregnancy - Data processing
Obstetrics - Data processing Artificial intelligence - Medical applications Artificial Intelligence Pregnancy Electronic Data Processing - methods |
| ISBN | 3-031-18154-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro -- Foreword -- Preface -- Contents -- 1 Baby Fever -- 1.1 Natality. Trends Through History -- 1.2 Where Are We Now? -- 1.2.1 Exploratory Data Analysis -- References -- 2 Planning a Pregnancy with Artificial Intelligence -- 2.1 Prenatal Tests -- 2.2 Fertility Issues -- References -- 3 "We're Pregnant!" Artificial Intelligence by Your Side -- 3.1 Miscarriage -- 3.2 First Trimester Ultrasound -- References -- 4 Second Trimester and Artificial Intelligence -- 4.1 Second Trimester Ultrasound -- 4.1.1 Fetal Echocardiography -- References -- 5 Third Trimester and Artificial Intelligence -- 5.1 Wellbeing Ultrasound -- 5.2 Preterm Labor -- References -- Untitled -- 6 Our Road Has Come to an End -- 6.1 Training for Labor and Delivery -- 6.2 Childbirth -- References -- 7 Perinatal Depression and Artificial Intelligence -- References -- Appendix-Statistical Tables -- Index. |
| Record Nr. | UNINA-9910627268203321 |
Belciug Smaranda
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| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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System design for epidemics using machine learning and deep learning / / G.R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra, editors
| System design for epidemics using machine learning and deep learning / / G.R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (336 pages) |
| Disciplina | 610.28563 |
| Collana | Signals and communication technology |
| Soggetto topico |
Artificial intelligence - Medical applications
Deep learning (Machine learning) - Therapeutic use Epidemics - Prevention - Technological innovations Deep learning (Machine learning) Epidemics - Prevention Deep Learning Machine Learning Epidemics - prevention & control Electronic Data Processing - methods |
| ISBN | 3-031-19752-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Pandemic effect of COVID-19: Identification, Present scenario and preventive measures using Machine learning model. -- 2. A Comprehensive Review of the Smart Health Records to prevent Pandemic -- 3. Automation of COVID-19 Disease Diagnosis from Radiograph -- 4. Applications of Artificial Intelligence in the attainment of Sustainable Development Goals -- 5. A Novel Model for IoT Blockchain Assurance Based Compliance to COVID Quarantine -- 6. DEEP LEARNING BASED CONVOLUTIONALNEURAL NETWORK WITH RANDOM FOREST APPROACH FOR MRI BRAIN TUMOUR SEGMENTATION -- 7. Expert systems for improving the effectiveness of remote health monitoring in Covid-19 Pandemic -- A Critical Review -- 8. Artificial Intelligence-based predictive tools for Life-threatening diseases -- 9. Deep Convolutional Generative Adversarial Network for Metastatic Tissue Diagnosis in Lymph Node Section -- 10. Transformation in Health Sector during Pandemic by Photonics Devices -- 11. DIAGNOSIS OF COVID-19 FROM CT IMAGES AND RESPIRATORY SOUND SIGNALS USING DEEP LEARNING STRATEGIES -- 12. The Role of Edge Computing in Pandemic and Epidemic Situations with its Solutions -- 13. Advances and application of Artificial Intelligence and Machine learning in the field of cardiovascular diseases and its role during the Pandemic condition -- 14. Effective Health Screening and Prompt Vaccination to Counter the Spread of Covid-19 and Minimize its Adverse Effects -- 15. CROWD DENSITY ESTIMATION USING NEURAL NETWORK FOR COVID'19 AND FUTURE PANDEMICS -- 16. "Role of digital healthcare in rehabilitation during pandemic" -- 17. AN EPIDEMIC OF NEURODEGENERATIVE DISEASE ANALYSIS USING MACHINE LEARNING TECHNIQUES -- 18. Covid-19 Growth Curve Forecasting for India using Deep Learning Techniques. |
| Record Nr. | UNINA-9910736996903321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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