Mammographic breast density is an established risk factor for breast cancer. However, results are inconclusive regarding its use in risk prediction models. The current study evaluated 13,409 postmenopausal participants in the NSABP Study of Tamoxifen and Raloxifene. A measure of breast density as reported on the entry mammogram report was extracted and categorized according to The American Coll...

Background: Prediction of breast cancer risk and identifying women who are at high risk of breast cancer, would be a great help for planning and conducting screening programs. The aim of this study was to estimate the 5-year breast cancer risk among women in Isfahan. Methods: This cross-sectional study was conducted on 9674 women aged 35-69 years who referred to the Breast Cancer Screening Cen...

Imitation learning aims at recovering expert policies from limited demonstration data. Generative Adversarial Learning (GAIL) employs the generative adversarial framework for imitation and has shown great potentials. GAIL its variants, however, are found highly sensitive to hyperparameters hard converge well in practice. One key issue is that supervised discriminator a much faster speed than re...

INTRODUCTION Breast cancer screening programmes are based on various risk models to assess the risk of breast cancer in the general population. The aim of the present study is to predict the efficacy of the Gail model (GM) in the Indian population. We did a retrospective calculation of the Gail score from the hospital records of patients with breast cancer and benign breast disease. MATERIALS...

Background: The Gail Model has been widely implemented in developed and developing countries and is considered to be the best available instrument to estimate breast cancer (BC) risk for early prevention. Objective: The goals of the study were to determine five-year and lifetime BC risks and to assess BC predictors among female Saudi teachers using the Gail model. Methods: A cross sectional stu...

PURPOSE We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. METHODS Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's ...

An open problem in autonomous vehicle safety validation is building reliable models of human driving behavior simulation. This work presents an approach to learn neural policies from real world demonstration data. We model as a sequential decision making that characterized by non-linearity and stochasticity, unknown underlying cost functions. Imitation learning for generating intelligent when t...

BACKGROUND Lifetime risk assessment tools are relatively limited in identifying breast cancer risk in younger women. The predictive value of mathematical models to estimate risk varies according to age, menopausal status, race/ethnicity, and family history. Current risk prediction models estimate population, not individual, levels of breast cancer risk; hence, individualized risk prediction mod...

BACKGROUND Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women....

Gail D. Adams was one of the founding members of both AAPM and ACMP. He helped shape the profession that all of us enjoy today. Gail had a major impact on scientific and professional activities. His pioneering efforts were felt in all areas of medical physics and radiation oncology. Gail was very clinical and he participated as a partner of the radiation oncologist in the radiation treatment pr...