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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Clinical Diagnosis Support With Convolutional Neural Network By Transfer Learning, Spencer Fogleman, Jeremy Otsap, Sangrae Cho
Clinical Diagnosis Support With Convolutional Neural Network By Transfer Learning, Spencer Fogleman, Jeremy Otsap, Sangrae Cho
SMU Data Science Review
Breast cancer is prevalent among women in the United States. Breast cancer screening is standard but requires a radiologist to review screening images to make a diagnosis. Diagnosis through the traditional screening method of mammography currently has an accuracy of about 78% for women of all ages and demographics. A more recent and precise technique called Digital Breast Tomosynthesis (DBT) has shown to be more promising but is less well studied. A machine learning model trained on DBT images has the potential to increase the success of identifying breast cancer and reduce the time it takes to diagnose a patient, …
Personalized Medicine: The Use Of Biomarkers And Molecularly Targeted Therapies For Patient Care And Cancer Intervention, Wafa Asad, Emily Schmitt Lavin
Personalized Medicine: The Use Of Biomarkers And Molecularly Targeted Therapies For Patient Care And Cancer Intervention, Wafa Asad, Emily Schmitt Lavin
Mako: NSU Undergraduate Student Journal
Personalized medicine and targeted therapy have been emerging fields of study for the remediation and inhibition of cancer. Personalized medicine in the treatment of cancer involves using genetic, immune, and proteomic profiling to provide therapeutic options as well as prognostic background for every patient and their tumor’s genetic mutations. Targeted therapies allow researchers and medical personnel alike to determine the appropriate treatment for a patient based on the molecular basis and mechanistic actions of a cancerous tumor. The overall significance of this study was to express how these treatments use biomarkers to pinpoint the location, and severity of the cancer, …
A Comparison Of Different Methods For Predicting Cancer Mortality Counts At The State Level, Corinne Wilson
A Comparison Of Different Methods For Predicting Cancer Mortality Counts At The State Level, Corinne Wilson
Virginia Journal of Science
Cancer is a major health issue in the United States. Reliable estimates of yearly cancer mortality counts are essential for resourcing and planning. The American Cancer Society has used several methods of forecasting to estimate the future cancer burden and researchers are continually working to develop new methods with improved performance. There have been studies comparing different models for predicting the US cancer mortality counts. This study explores and compares several different models for cancer mortality count predictions at the state level, principally for the state of Virginia. Results of the comparisons appear to show the final improved model to …