Description
Taylor and Francis Ltd Latest Advances in Diagnosis and Treatment of Women-Associated Cancers 1st Edition 2022 Hardbound by Rashid, Shazia
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. 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.