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Articles 1 - 3 of 3
Full-Text Articles in Survival Analysis
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
COBRA Preprint Series
One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …
The Association Between The Il-1 Pathway, Isaac C. Wun
The Association Between The Il-1 Pathway, Isaac C. Wun
Dissertations & Theses (Open Access)
Cutaneous malignant melanoma (CMM) is a potentially lethal malignancy that warrants attention and further research, as it is known to that there is an increasing rate of incidence in theUnited States, and it is also known that exposure to UV light is its most crucial risk factor, and family history of melanoma is also an important risk factor. Melanoma is an aggressive and lethal cancer in humans. There are an estimated new 132,000 melanoma cases annually worldwide, and the trend has doubled in the past 20 years. However, attempts to treat melanoma have encountered considerable resistance and remained ineffective. The …
Survival Prediction For Brain Tumor Patients Using Gene Expression Data, Vinicius Bonato
Survival Prediction For Brain Tumor Patients Using Gene Expression Data, Vinicius Bonato
Dissertations & Theses (Open Access)
Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. …