J
Jeffrey L. Solka
Researcher at Naval Surface Warfare Center
Publications - 65
Citations - 1278
Jeffrey L. Solka is an academic researcher from Naval Surface Warfare Center. The author has contributed to research in topics: Feature extraction & Image segmentation. The author has an hindex of 22, co-authored 64 publications receiving 1234 citations. Previous affiliations of Jeffrey L. Solka include United States Department of the Navy & George Mason University.
Papers
More filters
Journal ArticleDOI
Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography
K. Woods,Christopher C. Doss,Kevin W. Bowyer,Jeffrey L. Solka,Carey E. Priebe,W. Philip Kegelmeyer +5 more
TL;DR: This paper focuses on the classification of segmented local bright spots as either calcification or noncalcification in mammographic images and seven classifiers (linear and quadratic classifiers, binary decision trees, standard backpropagation network, 2 dynamic neural networks, and a K-nearest neighbor) are compared.
Journal ArticleDOI
A network-based approach to prioritize results from genome-wide association studies.
Nirmala Akula,Ancha Baranova,Donald Seto,Jeffrey L. Solka,Mike A. Nalls,Andrew B. Singleton,Luigi Ferrucci,Toshiko Tanaka,Stefania Bandinelli,Yoon Shin Cho,Young-Jin Kim,Jong-Young Lee,Bok-Ghee Han,Francis J. McMahon +13 more
TL;DR: Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data, efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.
Journal ArticleDOI
Literature-related discovery (LRD): Methodology
TL;DR: The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its O DS LBD component, is described in this paper and a comprehensive flow chart showing the details of the systematic potential discovery generation process is presented.
Journal ArticleDOI
The application of fractal analysis to mammographic tissue classification
Carey E. Priebe,Jeffrey L. Solka,Richard A. Lorey,George W. Rogers,Wendy L. Poston,Maria Kallergi,Wei Oian,Laurence P. Clarke,Robert A. Clark +8 more
TL;DR: Preliminary results indicate that discrimination based on the fractal nature of images may well represent a viable approach to utilizing computers to assist in diagnosis.
Journal ArticleDOI
Text Data Mining: Theory and Methods
TL;DR: The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of the interesting challenges that remain to be solved within the area.