Artificial intelligence in cancer diagnosis and prognosis. Volume 2, Breast and bladder cancer /

Within this second volume dealing with breast and bladder 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 ho...

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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.
Breast > Cancer > Diagnosis > Data processing.
Breast > Cancer > Treatment > Data processing.
Bladder > Cancer > Diagnosis > Data processing.
Bladder > Cancer > Treatment > Data processing.
Artificial intelligence > Medical applications.
Neoplasms > diagnosis.
Neoplasms > therapy.
Breast Neoplasms > diagnosis.
Breast Neoplasms > therapy.
Urinary Bladder Neoplasms > diagnosis.
Urinary Bladder Neoplasms > therapy.
Artificial Intelligence.
Technology, engineering, agriculture.
Biomedical engineering.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. Development of artificial neural networks for breast histopathological image analysis / Chen Li, Yuchao Zheng, Haiqing Zhang, Xiaomin Zhou, Yin Dai and Xiaoyan Li
  • 2. Machine learning in bladder cancer diagnosis / Elliot S. Kim, Valentina L. Kouznetsova and Igor F. Tsigelny
  • 3. Deep learning in photoacoustic breast cancer imaging / Changchun Yang and Fei Gao
  • 4. Histopathological breast cancer image classification with feature prioritization using a heuristic algorithm / Abdullah-Al Nahid, Johir Raihan, Niloy Sikder and Saifur Rahman Sabuj
  • 5. The use of machine learning and biofluid metabolomics in breast cancer diagnosis / Mashiro Sugimoto
  • 6. AUTO-BREAST : a fully automated pipeline for breast cancer diagnosis using AI technology / Nagia M. Ghanem, Omneya Attallah, Fatma Anwar and Mohamed A. Ismail
  • 7. Diagnosis of breast cancer from histopathological images using artificial intelligence / R. Rashmi, Keerthana Prasad and Chethana Babu K. Udupa
  • 8. The role of artificial intelligence in the field of bladder cancer / Agus Rizal A.H. Hamid, Prasandhya A. Yusuf and Anindya Pradipta
  • 9. Exploring data science paradigms in breast cancer classification : linking data, learning, and artificial intelligence in medical diagnosis / Shomona Gracia Jacob and Bensujin Bennet
  • 10. Automatic detection and classification of invasive ductal carcinoma in histopathology images using convolutional neural networks / R. Karthiga, K. Narasimhan and N. Raju
  • 11. Machine learning analysis of breast cancer single-cell omics data / Shenghua Tian and Tao Huang
  • 12. Radiomics, deep learning, and breast cancer detection / Y. Jiménez Gaona, M.J. Rodríguez-Álvarez, D. Castillo Malla and V. Lakshminarayanan
  • 13. Artificial-intelligence-based techniques for the diagnosis of bladder and breast cancer / Shadab Momin, Yang Lei, Tian Liu and Xiaofeng Yang.

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