Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^