Artificial intelligence in cancer diagnosis and prognosis. Volume 1, Lung and kidney cancer /

Within this first volume dealing with lung and kidney cancer, the editors and authors detail the latest research related to the application of artificial intelligence (AI) to cancer diagnosis and prognosis and summarize its advantages. It is the intention of the editors and authors to explore how AI...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: El-Baz, Ayman S. (Editor ), Suri, Jasjit S. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bristol [England] (No.2 The Distillery, Glassfields, Avon Street, Bristol, BS2 0GR, UK) : IOP Publishing, [2022]
Colección:IOP (Series). Release 22.
IPEM-IOP series in physics and engineering in medicine and biology.
IOP ebooks. 2022 collection.
Temas:
Cancer > Diagnosis > Data processing.
Cancer > Treatment > Data processing.
Lungs > Cancer > Diagnosis > Data processing.
Lungs > Cancer > Treatment > Data processing.
Kidneys > Cancer > Diagnosis > Data processing.
Kidneys > Cancer > Treatment > Data processing.
Artificial intelligence > Medical applications.
Neoplasms > diagnosis.
Neoplasms > therapy.
Lung Neoplasms > diagnosis.
Lung Neoplasms > therapy.
Kidney Neoplasms > diagnosis.
Kidney Neoplasms > therapy.
Artificial Intelligence.
Technology, engineering, agriculture.
Biomedical engineering.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. American Joint Committee on Cancer staging of lung and renal cancers using a recurrent deep neural network model / Dipanjan Moitra
  • 2. Neural-ensemble-based detection : a modern way to diagnose lung cancer / Sharayu Govardhane, Sahil Gandhi and Pravin Shende
  • 3. Computed tomography and magnetic resonance imaging machine learning applications for renal cell carcinoma / Elvira Guerriero, Arnaldo Stanzione, Lorenzo Ugga and Renato Cuocolo
  • 4. Pulmonary nodule-based feature learning for automated lung tumor grading using convolutional neural networks / Supriya Suresh and Subaji Mohan
  • 5. Detection of lung contours using closed principal curves and machine learning / Tao Peng, Yihuai Wang, Thomas Canhao Xu, Lianmin Shi, Jianwu Jiang and Shilang Zhu
  • 6. Bytes, pixels, and bases : machine learning in imaging-omics for renal cell carcinoma / Ruchi Chauhan, C.V. Jawahar and P.K. Vinod
  • 7. Detection, growth quantification, and malignancy prediction of pulmonary nodules using deep convolutional networks in follow-up CT scans / Xavier Rafael-Palou, Anton Aubanell, Mario Ceresa, Vicent Ribas, Gemma Piella and Miguel A González Ballester
  • 8. Training a deep multiview model using small samples of medical data / Junzhou Huang, Xinliang Zhu and Jiawen Yao
  • 9. Overview of deep learning for lung cancer diagnosis / Boran Sekeroglu, Daniel Chwaifo Malann and Kubra Tuncal
  • 10. Artificial intelligence for cancer diagnosis / Sura Khalil Abd, Mustafa Musa Jaber, Sarah Yahya Ali and Mohammed Hasan Ali
  • 11. Lung cancer diagnosis using 3D-CNN and spherical harmonics expansions / Ahmed Shaffie, Ahmed Soliman, Ali Mahmoud, Fatma Taher, Mohammed Ghazal and Ayman El-Baz.

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