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Endocrine Therapy in Breast Cancer
This reference evaluates and describes the latest strategies for hormone suppression and blockade in the management of early and advanced stage breast cancer and explores the effects of tamoxifen, selective estrogen receptor modulators (SERMs), aromatase inhibitors, and their combination on both breast cancers and normal tissues. Endocrine T
Endocrine Therapy in Breast Cancer
This reference evaluates and describes the latest strategies for hormone suppression and blockade in the management of early and advanced stage breast cancer and explores the effects of tamoxifen, selective estrogen receptor modulators (SERMs), aromatase inhibitors, and their combination on both breast cancers and normal tissues. Endocrine Therapy in Breast Cancer details modern techniques for molecular profiling, monitoring, and targeting offers methods to identify high-risk groups evaluates molecular biomarkers in breast cancer assessment examines the potential toxicity of estrogen receptor (ER)-directed endocrine therapy investigates the development of endocrine resistance discusses neoad...
Endocrine Therapy for Breast Cancer
Because of the predominant role estrogens play in the development of breast cancer and the limited effectiveness of tamoxifen therapy, more selective therapeutics targeting estrogen signaling have been developed: selective estrogen receptor modulators (SERMs), selective estrogen receptor downregulators (SERDs), and a third generation of drugs that inhibit the aromatase required for estrogen biosyntheses. The authors examine clinical and translational research results from studies of these endocrine therapies and chemotherapies in pre- and postmenopausal women with early and advanced breast cancer. Advances in Endocrine Therapy of Breast Cancer provides guidance on promising new therapeutics and treatment combinations based on compelling clinical evidence.
Medical Data Analysis and Processing using Explainable Artificial Intelligence
The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data Explores the concepts of natural langua...
