Analyzing Data Mining Statistical Models of Bio Medical

The main goal of this thesis is to investigate the preformance of different data mining models on Biomedical datasets (heart disease data). I used different data mining models as, neural networks, support vector machine and logictic regression will be executed on these datasets. Some performance metrics such as accurary, precision and recall will be calculated and recorded. I compare the data mining models by using the recorded values of the performance metrics to find the best model for the datasets

Network analysis of unstructured EHR data for clinical research.

In biomedical research, network analysis provides a conceptual framework for interpreting data from high-throughput experiments. For example, protein-protein interaction networks have been successfully used to identify candidate disease genes. Recently, advances in clinical text processing and the increasing availability of clinical data have enabled analogous analyses on data from electronic medical records. We constructed networks of diseases, drugs, medical devices and procedures using concepts recognized in clinical notes from the Stanford clinical data warehouse. We demonstrate the use of the resulting networks for clinical research informatics in two ways-cohort construction and outcomes analysis-by examining the safety of cilostazol in peripheral artery disease patients as a use case. We show that the network-based approaches can be used for constructing patient cohorts as well as for analyzing differences in outcomes by comparing with standard methods, and discuss the advantages offered by network-based approaches

The flight of the white collars

By analyzing two novel data sets from Turkey, we provide empirical evidence for yet another negative consequence of civil conflicts. We show that the long running civil cinflict in Turkey has been driving away doctors and other medical personnel from conflict areas, and the availability of medical personal is positively associated with public health. By doing so, we illuminate an important, yet never analyzed before mechanism through which civil conflicts exert their long-term negative influences on the most important "life chances" of societies, namely, the chance to lead a healthy life. We then proceed to provide some evidence that a similar dynamic is in play in education as well

Exploration of User Groups in VEXUS

We introduce VEXUS, an interactive visualization framework for exploring user data to fulfill tasks such as finding a set of experts, forming discussion groups and analyzing collective behaviors. User data is characterized by a combination of demographics like age and occupation, and actions such as rating a movie, writing a paper, following a medical treatment or buying groceries. The ubiquity of user data requires tools that help explorers, be they specialists or novice users, acquire new insights. VEXUS lets explorers interact with user data via visual primitives and builds an exploration profile to recommend the next exploration steps. VEXUS combines state-of-the-art visualization techniques with appropriate indexing of user data to provide fast and relevant exploration