Current Search: Breast -- Cancer -- Risk factors (x)
-
-
Title
-
Efficient Machine Learning Algorithms for Identifying Risk Factors of Prostate and Breast Cancers among Males and Females.
-
Creator
-
Rikhtehgaran, Samaneh, Muhammad, Wazir, Florida Atlantic University, Department of Physics, Charles E. Schmidt College of Science
-
Abstract/Description
-
One of the most common types of cancer among women is breast cancer. It represents one of the diseases leading to a high number of mortalities among women. On the other hand, prostate cancer is the second most frequent malignancy in men worldwide. The early detection of prostate cancer is fundamental to reduce mortality and increase the survival rate. A comparison between six types of machine learning models as Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, k Nearest...
Show moreOne of the most common types of cancer among women is breast cancer. It represents one of the diseases leading to a high number of mortalities among women. On the other hand, prostate cancer is the second most frequent malignancy in men worldwide. The early detection of prostate cancer is fundamental to reduce mortality and increase the survival rate. A comparison between six types of machine learning models as Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, k Nearest Neighbors, and Naïve Bayes has been performed. This research aims to identify the most efficient machine learning algorithms for identifying the most significant risk factors of prostate and breast cancers. For this reason, National Health Interview Survey (NHIS) and Prostate, Lung, Colorectal, and Ovarian (PLCO) datasets are used. A comprehensive comparison of risk factors leading to these two crucial cancers can significantly impact early detection and progressive improvement in survival.
Show less
-
Date Issued
-
2021
-
PURL
-
http://purl.flvc.org/fau/fd/FA00013755
-
Subject Headings
-
Machine learning, Algorithms, Cancer--Risk factors, Breast--Cancer, Prostate--Cancer
-
Format
-
Document (PDF)
-
-
Title
-
Anticarcinogenic effects of genistein and anthocyanin extract in MCF-7 human breast cancer cells.
-
Creator
-
Stinson, Corine M., Charles E. Schmidt College of Science, Department of Biological Sciences
-
Abstract/Description
-
This study investigated potential apoptotic and anti-proliferative effects of the phytochemicals, genistein and anthocyanin extract, as single and combined treatments in MCF-7 human breast cancer cells. Cells were exposed to single and combined treatments with the phytochemiclas for 48 and 72 hours. Cell viability was assessed using the MTT bioassay. Apoptosis induction was assessed using acridine orange ethidium bromide and rhodamine 123 ethidium bromide fluorescence assays. Both singe and...
Show moreThis study investigated potential apoptotic and anti-proliferative effects of the phytochemicals, genistein and anthocyanin extract, as single and combined treatments in MCF-7 human breast cancer cells. Cells were exposed to single and combined treatments with the phytochemiclas for 48 and 72 hours. Cell viability was assessed using the MTT bioassay. Apoptosis induction was assessed using acridine orange ethidium bromide and rhodamine 123 ethidium bromide fluorescence assays. Both singe and combination treatments induced dose- and time-dependent apoptotic cell death in MCF-7 cells. The percentage of apoptosis was higher in combination treatments than single treatments with either phytochemical, although the difference was not statistically significant. The combination of genistein and anthocyanin extract peaked in efficacy at 48 hours of treatment, to exhibit significantly greater (P<. O5) dose- and time-dependent cell cytotoxicity than single treatments. This study reveals potential chemopreventive implications for the complementary effects of genistein and anthocyanin extract.
Show less
-
Date Issued
-
2011
-
PURL
-
http://purl.flvc.org/FAU/3320108
-
Subject Headings
-
Phytochemicals, Therapeutic use, Phytoestrogens, Physiological effect, Breast, Cancer, Risk factors, Breast, Cancer, Treatment, Probiotics, Cancer, Chemoprevention, Antioxidants, Therapeutic use
-
Format
-
Document (PDF)
