A MACHINE LEARNING-BASED QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP STUDY FOR THE ANTICANCER ACTIVITY OF A SERIES OF COMPOUNDS
Abstract
Cancer is a collective term used to describe a group of different diseases that are characterized by the loss of control of cell growth and division, leading to a primary tumor that invades and destroys adjacent tissues. It may also spread to other regions of the body through a process known as metastasis, which is the cause of 90% of cancer deaths. Cancer remains one of the most difficult diseases to treat and is responsible for approximately 14.5% of all deaths worldwide. Breast cancer is the most frequent malignancy in females. Due to its major impact on population, this disease represents a critical public health problem that requires further research at the molecular level in order to define its prognosis and specific treatment. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% of the total cancer cases and 14% of the cancer deaths; thus, research in this field is important to overcome both economical and psychological burden.
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