A modern approach of survival analysis of patients with pancreatic cancer.

Pancreatic cancer is one of the deadliest diseases and becoming an increasingly common cause of cancer mortality. It continues to give rise to massive challenges to clinicians and cancer researchers. One of the main goals of our present study is to determine if there exists any statistically significant difference in the survival probabilities of male and female pancreatic cancer patients in different cancer stages and irrespective of stages.

Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks.

Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias, and learning discriminating boundaries between the minority and majority classes could be challenging. To address the class distribution imbalance in deep learning, we propose a class rebalancing strategy based on a class-balanced dynamically weighted loss function where weights are assigned based on the class frequency and predicted probability of ground-truth class.

A Statistical Study of Serum Cholesterol Level by Gender and Race.

Background: Cholesterol level (CL) is growing concerned as health issue in human health since it is considered one of the causes in heart diseases. A study of cholesterol level can provide insight about its nature and characteristics.

Study Design: A cross-sectional study.

Histological and Demographic Characteristics of the Distribution of Brain and Central Nervous System Tumors' Sizes: Results from SEER Registries Using Statistical Methods.

The examination of brain tumor growth and its variability among cancer patients is an important aspect of epidemiologic and medical data. Several studies for tumors of brain interpreted descriptive data, in this study we perform inference in the extent possible, suggesting possible explanations for the differentiation in the survival rates apparent in the epidemiologic data. Population based information from nine registries in the USA are classified with respect to age, gender, race and tumor histology to study tumor size variation.

A join point survival model for brain tumor patients.

To investigate the relationship between medical improvements and the survival experienced by the patient population, it would be useful to find out when and how much the cancer treatment breakthroughs and early diagnosis have significantly improved the prognosis of brain cancer patients. A join point model facilitates the identification of trends with significant change-points in survival; the main goal of such a model would be to find out when cancer survival starts exhibiting a pattern of improvement. The model will be applied to grouped relative survival data for major cancer sites from the 'Surveillance, epidemiology and end results' program of the National Cancer Institute.

Statistical modeling of lung cancer: answering relative questions.

THE OBJECTIVE OF THIS PAPER IS TO PERFORM PARAMETRIC AND NONPARAMETRIC ANALYSIS TO ADDRESS SOME VERY IMPORTANT QUESTIONS CONCERNING LUNG CANCER UTILIZING REAL LUNG CANCER DATA: What is the probabilistic nature of mortality time in ex-smoker lung cancer patients and non-smoker lung cancer patients, for female, male, and the totality of female and male patients? Is there significant difference of mortality time between ex-smoker and non-smoker patients? For ex-smokers, are there any differences with respect to the key variables such as mortality time, cigarettes per day (CPD), and duration of smoking between female and male patients? For non-smokers, can we notice a difference in mortality time between female and male patients? Can we accurately predict mortality time given information on CPD, starting time and quitting time for a specific lung cancer patient who smokes? Thus best fitting probability distributions are identified and their parameters are estimated. Mean mortality times are compared between non-smokers and ex-smokers, female non-smokers and male non-smokers, and female ex-smokers and male ex-smokers. Important entities related to lung cancer mortality time, such as cigarettes per day (CPD), and duration of smoking (DUR), are compared between female and male ex-smoker lung cancer patients.