Medicine and Health Sciences Commons^™

The Spatial Distribution Of Cancer Incidence In Fars Province: A Gis-Based Analysis Of Cancer Registry Data, Ali Goli, Mahbobeh Oroei, Mehdi Jalalpour, Hossein Faramarzi, Mehrdad Askarian

Civil and Environmental Engineering Faculty Publications

Background: Cancer is a major health problem in the developing countries. Variations of its incidence rate among geographical areas are due to various contributing factors. This study was performed to assess the spatial patterns of cancer incidence in the Fars Province, based on cancer registry data and to determine geographical clusters.

Methods: In this cross sectional study, the new cases of cancer were recorded from 2001 to 2009. Crude incidence rate was estimated based on age groups and sex in the counties of the Fars Province. Age standardized incidence rates (ASR) per 100,000 was calculated in each year. …

Microspheres For Liver Radiomicrospheres Therapy And Planning, Alejandro Amor-Coarasa

FIU Electronic Theses and Dissertations

Liver cancer accounts for nearly 10% of all cancers in the US. Intrahepatic Arterial Radiomicrosphere Therapy (RMT), also known as Selective Internal Radiation Treatment (SIRT), is one of the evolving treatment modalities. Successful patient clinical outcomes require suitable treatment planning followed by delivery of the microspheres for therapy. The production and in vitro evaluation of various polymers (PGCD, CHS and CHSg) microspheres for a RMT and RMT planning are described. Microparticles with a 30±10 µm size distribution were prepared by emulsion method. The in vitro half-life of the particles was determined in PBS buffer and porcine plasma and their potential …

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …