background: diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. missing data is an issue that challenges the model making. the aim of this study was to develop a diagnostic model to predict death in hiv/ aids patients when missing data exist. methods: hiv patients (n=1460) referred to voluntary consoling and testing cen...

in interventional or observational longitudinal studies, the issue of missing values is one of the main concepts that should be investigated. the researcher's main concerns are the impact of missing data on the final results of the study and the appropriate methods that missing values should be handled. regarding the role and the scale of the variable that missing values have been occurred and ...

Learning with uncertain inputs is well-known to be a difficult task. In order to achieve this analytically using a Gaussian Process prior model, we expand the original process around the input mean (Delta method), assuming the random input is normally distributed. We thus derive a new process whose covariance function accounts for the randomness of the input. We illustrate the effectiveness of ...

Power outages present a significant threat to all of humanity. However, elements critical infrastructure are most affected by this event. Among other things, healthcare facilities can be considered infrastructure. They the backbone for saving lives. even these medical endangered. The primary aim paper is design an algorithm assess solve power outages. Several inputs evaluation facilities. Based...

Background Policy makers need models to be able to detect groups at high risk of HIV infection. Incomplete records and dirty data are frequently seen in national data sets. Presence of missing data challenges the practice of model development. Several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. One of the issues which was of less concern...

background: the aim of the article is demonstrating an application of multiple imputation (mi) for handling missing clinical data in the setting of rheumatologic surveys using data derived from 10291 people participating in the first phase of the community oriented program for control of rheumatic disorders (copcord) in iran . methods: five data subsets were produced from the original data set....

What is consciousness and what is the missing link between the sensory input and the cortical centre in the brain for consciousness? In the literature there are more than a million pages written about consciousness. The perspectives range from the field of metaphysics to those of quantum mechanics. However, no one today has produced a theory which is universally accepted. Consciousness is “some...

The changing economic conditions have challenged many financial institutions to search for more efficient and effective ways to assess emerging markets. Data Envelopment Analysis (DEA) is a widely used mathematical programming technique that compares the inputs and outputs of a set of homogenous Decision Making Units (DMUs) by evaluating their relative efficiency. In the conventional DEA model,...

Individuals born without one hand (congenital one-handers) provide a unique model for understanding the relationship between focal reorganization in the sensorimotor cortex and everyday behavior. We previously reported that the missing hand's territory of one-handers becomes utilized by its cortical neighbor (residual arm representation), depending on residual arm usage in daily life to substit...