Machine Learning-Based Evaluation of Breast Cancer Risk Linked to Environmental Pollutant Exposure
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Cancer continues to be a human affliction and is brought on by aberrant cells that divide out of control. Cancers get their name from the word crab (a Latin word); as a result, they attach to every region of the body obstinately, just like crabs do. Thus, the malignant growth has the potential to penetrate and damage neighboring structures, and spread to faraway locations, ultimately leading to death. Cancer, in both sexes and at all ages, can affect all living cells within the body. Multiple factors are involved in causing the disease [1]. Cancer is a global burden that is projected to rise as a result of human proliferation and age, as well as the adoption of cancer-causing lifestyles. Malignancies with a historically low prevalence, such as female breast, colorectal, and lung cancers, are becoming more common in economically developing nations [2]. The type of cancer that has been observed with prominent occurrence and fatality in men is lung cancer, which is preceded by prostate and colorectal cancer (on the basis of prevalence) and stomach and liver cancer (on the basis of fatality rate). Contrarily, breast cancer (BC) has been reported with the most occurrence and is responsible for causing mortality in females, trailed by colorectal and lung cancers (incidence wise); cervical cancer ranks 4th (mortality and incidence wise) [3]. Cancer is also accountable for 1 out of 3 premature fatalities attributable to non-communicable diseases worldwide and it is expected that this count will increase every year [4]. Lung cancer is a very prevalent kind of malignancy and a significant reason of cancer mortality in males. The preponderance of women's cancer cases is still diagnosed with BC and contributes as a factor to female deaths. Nearly 2.1 million cases of breast malignancy in women are identified globally in the year 2018, representing one out of four cancer cases in females [2].

Kategorie: Taschenbuch Taschenbuch > Mathematik, Naturwissenschaft & Technik > Medizin & Pharmazie > Allgemeines & Lexika
Schlüsselwörter: Machine Learning-Based Evaluation of Breast Cancer Risk Linked to Environmental Pollutant Exposure;Sharma, Akriti;9798224182565
Daten vom 29.03.2024 02:00h
ISBN (andere Schreibweisen): 8-224-18256-8, 979-8-224-18256-5