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Computational Intelligence for Oncology and Neurological Disorders. Current Practices and Future Directions

ISBN: 9781032584577
Εκδόσεις:
Διαστάσεις 25 × 18 cm
Μορφή

Hardback

Εκδόσεις

Ημ. Έκδοσης

2024/07

Σελίδες

290

Έκδοση

1η έκδοση

Κύριος Συγγραφέας

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124,00€(Περιλαμβάνεται ΦΠΑ 6%)

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Περιγραφή

With the advent of computational intelligence-based approaches, such as bio-inspired techniques, and availability of clinical data from various complex experiments, medical consultants, researchers, neurologists, and oncologists, there is huge scope for CI-based applications in medical oncology and neurological disorders. This book focuses on interdisciplinary research in this field, bringing together medical practitioners dealing with neurological disorders and medical oncology along with CI investigators.

The book collects high-quality original contributions, containing the latest developments or applications of practical use and value, presenting interdisciplinary research and review articles in the field of intelligent systems for computational oncology and neurological disorders. Drawing from work across computer science, physics, mathematics, medical science, psychology, cognitive science, oncology, and neurobiology among others, it combines theoretical, applied, computational, experimental, and clinical research. It will be of great interest to any neurology or oncology researchers focused on computational approaches.

Περιεχόμενα

Chapter 1: Advancements in AI for Mental Health: Exploring ASD, ADHD and Schizophrenia,Video Datasets, and Future Directions

Charvi Bannur, Chaitra Bhat, Gagan Goutham, Mamatha H.R., Sada Kakarla

Chapter 2: Blockchain Applications in Neurological Disorders and Oncology

Gençay Sevim

Chapter 3: Deep Scattering Wavelet Network and Marine Predators Algorithm-Based Stuttering Disfluency Detection

Roohum Jegan, Bhakti Kaushal, Gajanan K. Birajdar, and Mukesh D. Patil

Chapter 4: AI in Neurological Disorders: A Systematic Review

Shashwati Mishra and Gobinda Chandra Panda

Chapter 5: Malformation Risk Prediction with Machine Learning Modelling for Pregnant Women with Epilepsy

Tessy Mathew, Jesna Mohan, Jisha Joh, Deepa P. L., and Sanjeev V. Thomas

Chapter 6: The Computational Techniques In Mutational Disease Prediction: A Comprehensive and Comparative Review

Lopamudra Das, Aruna Tripathy, Sarita Nanda, and J. K. Das

Chapter 7: Comparative Analysis of U-Net and DeepLab for Accurate Brain MRI Segmentation

Soumya Ranjan Mahanta and Mrutyunjaya Panda

Chapter 8: A Comprehensive Review on Depression Detection Based on Text from Social Media Posts

Vankayala Tejaswini, Bibhudatta Sahoo, and Korra Sathya Babu

Chapter 9: Artificial Intelligence in Radiation Oncology

Ashwani Kumar Aggarwal

Chapter 10: A Comprehensive Overview of AI Applications in Radiation Oncology

Neel Ghoshal and B.K. Tripathy

Chapter 11: Melanoma Skin Cancer Identification on Embedded Devices Using Digital Hair Removal and Transfer Learning

Shinde Rupali Kiran and Nam Kim

Chapter 12: A Deep Hybrid System for Effective Diagnosis of Breast Cancer

Adyasha Sahu, Pradeep Kumar Das, and Sukadev Meher

Chapter 13: Identification of Brain Cancer Using Medical Hyperspectral Image Analysis

Aloke Datta and Raj Bahadur Singh

Chapter 14: An Efficient Deep CNN-Based AML Detection: Overcoming small Database Limitations in Medical Applications

Pradeep Kumar Das, Adyasha Sahu, and Sukadev Meher

Chapter 15: Effective Use of Computational Biology and Artificial Intelligence in the Domain of Medical Oncology

Sameeksha Saraf, Arka De, and B. K. Tripathy

Chapter 16: A Computer-Aided Ensemble Method for Early Diagnosis of Coronary Artery Disease

Arkashree P. Mishra and Suvasini Panigrahi