Computational Intelligence for Clinical Diagnosis
This book contains multidisciplinary advancements in healthcare and technology through artificial intelligence (AI). The topics are crafted in such a way to cover all the areas of healthcare that require AI for further development. Some of the topics that contain algorithms and techniques are explai...
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| Format: | Elektronički e-knjiga |
| Jezik: | engleski |
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Springer International Publishing : Imprint: Springer,
2023.
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| Izdanje: | 1st ed. 2023. |
| Serija: | EAI/Springer Innovations in Communication and Computing,
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| Teme: | |
| Online pristup: | https://doi.org/10.1007/978-3-031-23683-9 |
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| 245 | 1 | 0 | |a Computational Intelligence for Clinical Diagnosis |h [electronic resource] / |c edited by Ferdin Joe John Joseph, Valentina Emilia Balas, S. Suman Rajest, R. Regin. |
| 250 | |a 1st ed. 2023. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2023. | |
| 300 | |a 1 online resource (XVIII, 592 p. 1 illus.). | ||
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| 490 | 1 | |a EAI/Springer Innovations in Communication and Computing, |x 2522-8609 | |
| 505 | 0 | |a 1. A Novel Approach for Multi class Brain Tumor Classification in MRI Images -- 2. Chicken Swarm-based Feature Selection with Optimal Deep Belief Network for Thyroid Cancer Detection and Classification -- 3. Efficient Method for Predicting Thyroid Disease Classification Using Support Vector Machine Compared Over Logistic Regression -- 4. Optimization of Management Response Towards Airborne Infections -- 5. Adaptive Sailfish Optimization- Contrast Limited Adaptive Histogram Equalization (ASFO-CLAHE) For Hyperparameter Tuning in Image Enhancement -- 6. Efficient Method for Predicting Thyroid Disease Classification Using Convolutional Neural Network Compared Over Support Vector Machine -- 7. Deep Learning in Healthcare Informatics -- 8. Detection of Breast Cancer Diagnosis Algorithm Based On TWCNN Technique -- 9. Internet of Things (IoT) and Artificial Intelligence (AI) to detect Urinary Tract Infections -- 10. Early Detection and Analysis of Diabetics and Non-Diabetics Using Machine Learning -- 11. An Intelligent Air Quality Prediction System Using Neuro-Fuzzy Temporal Classifier with Spatial Constraints -- 12. An Analysis of the Use of Machine Learning in the Diagnosis of Autism Spectrum Disorder -- 13. A Cost-Effective, Agar-Based Phantom for Thermogram Guided Malignancy Analysis -- 14. Multimodality Brain Tumor Image Fusion Using Wavelet and Contourlet Transformation -- 15. Performance based analysis of K-Medoids and K-Means Algorithms for the Diagnosis and Prediction of Oral Cancer -- 16. Comparative Correlation of Markers of Inflammatory Metamorphism in The Peripheral Blood of Patients with Dorsopathies of Different Genesis -- 17. AIOps Observability and Performance Impact of AI and ML Applications for Central Nervous System Drug Discoveries -- 18. Prediction and Classification of Aerosol Deposition in Lung Using CT Scan Images -- 19. Fusing Medical Images Using Pyramid Decomposition by DLCNN Method -- 20. 3D Cyst Sonomammogram Projection Using Reflection Coefficient and Mass Density in Python -- 21. Contrast Enhancement of Digital Mammograms Based on High Contrast-Limited Adaptive Histogram Equalization -- 22. A Pipelined Framework for the Prediction of Cardiac Disease with Dimensionality Reduction -- 23. Dispensable Microsystem Technology for Cancer Diagnosis -- 24. Segmentation of Attributes of The Skin Lesion Using Deep Ensemble Models -- 25. The Role of Emotional Intelligence During A Pandemic Crisis -- 26. Efficient Maintenance of Hospital Records by Entrusted Proof of Work (PoW) Algorithm in Block Chain Technology -- 27. Promethean Utilization of Resources Using Honeybee Optimization Techniques in Cloud Computing with Reference to Pandemic Healthcare -- 28. Healthcare Operational Intellectual Ability in Analysing the Factors Affecting Employee Churn -- 29. Impact on Social Work Practise and Research of Technology, Religion, and HIV/AIDS in India -- 30. Detection of Anomalies in Internet of Things (IoT) Network Using Artificial Neural Intelligence for Healthcare -- 31. Evaluation of Antiulcer Potentiality of D-Alpha-Tocopheryl Succinate by Inhibition of Oxidative Stress and Proinflammatory Cytokines -- 32. An Intelligent Air Quality During COVID-19 Prediction and Monitoring System Using Temporal CNN-LSTM -- 33. Implementation of a 'Useful' Information Measure for Healthcare Decision Making -- 34. Indian Sign Language Recognition Using Surf Feature Extraction and MDAE for Patient Disability Discussion -- 35. The Security Constructions and Enhancements of Smart Wearable Devices in Modern Technologies and Health Monitoring System -- 36. Hinokitiol attenuates LPS-induced arthritic inflammation – A Preclinical perspective -- 37. Development of Release Modulated Oxaceprol Topical Niosomal Gel: Assessment of Formulation Parameters and Performance Aspects -- 38. Using ICT Technologies, Open-Source Software Affects DHH Healthcare Issues -- 39. Clinical Intelligence for Cloud Services Resource Scheduling using RNN -- 40. The Capability ofObserving Performance in Healthcare Systems -- 41. Prediction of Lung Cancer from Electronic Health Records Using CNN Supported NLP -- 42. Challenges and Opportunities for IoT Deployment in India’s Healthcare Sector -- 43. WADET: A Novel Approach to Chronic Kidney Disease Detection and Analysis. | |
| 520 | |a This book contains multidisciplinary advancements in healthcare and technology through artificial intelligence (AI). The topics are crafted in such a way to cover all the areas of healthcare that require AI for further development. Some of the topics that contain algorithms and techniques are explained with the help of source code developed by the chapter contributors. The book covers the advancements in AI and healthcare from the Covid 19 pandemic and also analyzes the readiness and need for advancements in managing yet another pandemic in the future. Most of the technologies addressed in this book are added with a concept of encapsulation to obtain a cookbook for anyone who needs to reskill or upskill themselves in order to contribute to an advancement in the field. This book benefits students, professionals, and anyone from any background to learn about digital disruptions in healthcare. Contains multidisciplinary advancements in healthcare and technology throughartificial intelligence; Studies advancements in technology during Covid and assesses the readiness and need for advancements in managing future crises; Includes source code developed for topics which contain algorithms. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Telecommunication. | |
| 650 | 0 | |a Medical informatics. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 1 | 4 | |a Communications Engineering, Networks. |
| 650 | 2 | 4 | |a Health Informatics. |
| 650 | 2 | 4 | |a Computational Intelligence. |
| 700 | 1 | |a Joseph, Ferdin Joe John. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Balas, Valentina Emilia. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Rajest, S. Suman. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Regin, R. |e editor. |0 (orcid)0000-0002-6618-205X |1 https://orcid.org/0000-0002-6618-205X |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031236822 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031236846 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031236853 |
| 830 | 0 | |a EAI/Springer Innovations in Communication and Computing, |x 2522-8609 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-23683-9 |
| 912 | |a ZDB-2-ENG | ||
| 912 | |a ZDB-2-SXE | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||