Computational intelligence in cancer diagnosis : progress and challenges /
Computational Intelligence in Cancer Diagnosis: Progress and Challenges provides insights into the current strength and weaknesses of different applications and research findings on computational intelligence in cancer research. The book improves the exchange of ideas and coherence among various com...
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| Format: | eBook |
| Language: | English |
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London ; San Diego, CA :
Academic Press, an imprint of Elsevier,
[2023]
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| Edition: | First edition. |
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Part 1: Introduction to computational intelligence approaches
- The roadmap to the adoption of computational intelligence in cancer diagnosis: The clinical-radiological perspective / Federica Vernuccio, Roberto Cannella, Roberto Lagalla, and Massimo Midiri
- Deep learning approaches for high dimension cancer microarray data feature prediction: A review / Debasish Swapnesh Kumar Nayak, Subhashree Mohapatra, David Al-Dabass, and Tripti Swarnkar
- Integrative data analysis and automated deep learning technique for ovary cancer detection / Soutrik Acharya, Dyuti Ghosh, H. Swapnarekha, Manohar Mishra, and SoumyaRanjan Nayak
- Learning from multiple modalities of imaging data for cancer diagnosis / Liping Song, Shuai Liu, and Xiangbin Liu
- Neural network for lung cancer diagnosis / Shuai Liu, Liping Song, and Xiangbin Liu
- Machine learning for thyroid cancer diagnosis / Feyzullah Temurtas, Kutlucan Gorur, Onursal Cetin,and Ilyas Ozer
- Part 2: Prediction of cancer susceptibility
- Machine learning-based detection and classification of lung cancer / Shubham Dodia and B. Annappa
- Deep learning techniques for oral cancer diagnosis / Ijaz Ul Haq, Fath U Min Ullah, Khan Muhammad, and Sung Wook Baik
- An intelligent deep learning approach for colon cancer diagnosis / Pemmada Suresh Kumar, K. Anisha Kumari and Uttam Ghosh
- Effect of COVID-19 on cancer patients: Issues and future challenges / H. Swapnarekha and Janmenjoy Nayak
- Empirical wavelet transform-based fast deep convolutional neural network for detection and classification of melanoma / Bhanja Kishor Swain, Mrutyunjaya Sahani and Renu Sharma
- Part 3: Advance computational intelligence paradigms
- Convolutional neural networks and stacked generalization ensemble method in breast cancer prognosis / Tahmina Akter Tisha, Mir Moynuddin Ahmed Shibly, Kowshik Ahmed, and Shamim H. Ripon
- Light-gradient boosting machine for identification of osteosarcoma cell type from histological features / Etuari Oram, Pandit Byomakesha Dash and Bighnaraj Naik
- Deep learning-based computer-aided cervical cancer diagnosis in digital histopathology images / Pandia Rajan Jeyaraj, Edward Rajan Samuel Nadar and Bijaya Ketan Panigrahi
- Deep learning techniques for hepatocellular carcinoma diagnosis / Dillip Kumar Bishi, Priyadarshini Padhi, Chhabi Rani Panigrahi, Bibudhendu Pati, and Chandi Charan Rath
- Issues and future challenges in cancer prognosis: (Prostate cancer: A case study) / Dukka Karun Kumar Reddy, H. Swapnarekha, H.S. Behera, S. Vimal, Asit Kumar Das, and Danilo Pelusi
- A novel cancer drug target module mining approach using nonswarm intelligence / R. Gowri and R. Rathipriya.