Fr. 86.00

Latest Advances in Diagnosis and Treatment of Women-Associated Cancers

English · Hardback

Shipping usually within 1 to 3 weeks (not available at short notice)

Description

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There has been tremendous progress in cancer diagnosis and treatment methodologies, and this book focuses on major cancers of the cervix, breast, endometrium, and the associated reproductive system affecting women. It focuses on specific diagnostic techniques and treatment strategies including computational tools, Nanomedicine, and the use of Machine Learning (ML), Artificial Intelligence (AI), Big Data, and other latest techniques, including the evolution of these treatments over the years. Oncologists, cancer scientists, and professionals will find using the content on cutting-edge interventions by experts in their field, significantly improving earlier diagnosis and treatment options.

Key Features:
¿ Helps to improve quality of life after treatment as the focus of healthcare is shifting from curative methods to primary prevention of diseases, screening methods and early detection and treatment.
¿ Appeals to clinicians and residents interested in exploring cutting-edge technology for early diagnoses and treatment of women associated cancers.
¿ Features a chapter on the Clinician's perspective on advanced diagnostic and treatment methods.

List of contents










Preface. Acknowledgements. About the Editors. List of Contributors. List of Abbreviations. Glossary. Overview of Traditional Methods of Diagnosis and Treatment for Women-Associated Cancers. Cancer Drugs and Treatment Formulations for Women-Associated Cancers. Imaging as an Important Tool for Diagnosis of Breast Cancer. Use of Immunotherapy in Gynaecological and Breast Cancer. Computational Drug Discovery and Development Along With Their Applications in the Treatment of Women-Associated Cancers. Advances in Nanotechnology for Treatment of Women-Specific Cancers. Identifying Breast Cancer Treatment Biomarkers Using Transcriptomics. Integrating CADD and Herbal Informatics Approach to Explore Potential Drug Candidates Against HPV E Associated With Cervical Cancer. Advances in Big Data and Machine Learning in Cancer Detection in Women-Associated Cancers. Clinicians' Perspective in the Use and Adaptability of the Latest Methods of Diagnosis and Treatment for Cancers in Women. Index.


About the author










Dr. Shazia Rashid is an academician, working as an Assistant Professor at the Amity Institute of Biotechnology (AIB) and Adjunct Faculty at the Amity Institute of Molecular Medicine and Stem Cells (AIMMSCR), Amity University Uttar Pradesh, Noida, India.
Dr. Ankur Saxena is currently working as an Assistant Professor at Amity University Uttar Pradesh, Noida
Dr. Sabia Rashid is currently working as a consultant hematologist at Queen Elizabeth Hospital and Kings College Hospital in London, UK


Summary

There has been tremendous progress in cancer diagnosis and treatment methodologies, and this book focusses on major cancers of cervix, breast, endometrium, and the associated reproductive system affecting women, using computational tools, Nano medicine, Machine Learning (ML), Artificial Intelligence (AI), Big Data and other latest techniques.

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