• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 11
  • 7
  • 1
  • 1
  • Tagged with
  • 28
  • 28
  • 20
  • 20
  • 20
  • 10
  • 8
  • 8
  • 5
  • 5
  • 4
  • 4
  • 4
  • 3
  • 3
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A preliminary systems design for a community health data system

Moore, William Weldon, 1943- January 1972 (has links)
No description available.
2

Distributed development of a logic-based controlled medical terminology

Campbell, Keith Eugene. January 1997 (has links)
Thesis (Ph. D.)--Stanford University, 1997. / eContent provider-neutral record in process. Description based on print version record.
3

Distributed development of a logic-based controlled medical terminology

Campbell, Keith Eugene. January 1997 (has links)
Thesis (Ph. D.)--Stanford University, 1997.
4

Transformation-based approach to resolving data heterogeneity

Bychkov, Yury Alexandrovich. 10 April 2008 (has links)
No description available.
5

A comparison of relational and network data base representations of a medical repository system

Boswell, Paula S January 2010 (has links)
Typescript, etc. / Digitized by Kansas Correctional Industries
6

Network biology and machine learning approaches to metastasis and treatment response

Lubbock, Alexander Lyulph Robert January 2014 (has links)
Cancer causes 13% of human deaths worldwide, 90% of which involve metastasis. The reactivation of embryonic processes in epithelial cancers—and the epithelial-mesenchymal transition (EMT) in particular—results in increased cell motility and invasiveness, and is a known mechanism for initiating metastasis. The reverse process, the mesenchymal-epithelial transition (MET), is implicated in the process of cells colonising pre-metastatic niches. Understanding the relationships between EMT, MET and metastasis is therefore highly relevant to cancer research and treatment. Key challenges include deciphering the large, uncharted space of gene function, mapping the complex signalling networks involved and understanding how the EMT and MET programmes function in vivo within specific environments and disease contexts. Inference and analysis of small-scale networks from human tumour tissue samples, scored for protein expression, provides insight into pleiotropy, complex interactions and context-specific behaviour. Small sets of proteins (10–50, representative of key biological processes) are scored using quantitative antibody-based technologies (e.g. immunofluorescence) to give static expression values. A novel inference algorithm specifically for these data, Gabi, is presented, which produces signed, directed networks. On synthetic data, inferred networks often recapitulate the information flow between proteins in ground truth connectivity. Directionality predictions are highly accurate (90% correct) if the input network structure is itself accurate. The Gabi algorithm was applied to study multiple carcinomas (renal, breast, ovarian), providing novel insights into the relationships between EMT players and fundamental processes dysregulated in cancers (e.g. apoptosis, proliferation). Survival analysis on these cohorts shows further evidence for association of EMT with poor outcome. A patent-pending method is presented for stratifying response to sunitinib in metastatic renal cancer patients. The method is based on a proportional hazards model with predictive features selected automatically using regularisation (Bayesian information criterion). The final algorithm includes N-cadherin expression, a determinant of mesenchymal properties, and shows significant predictive power (p = 7.6x10-7, log-rank test). A separate method stratifies response to tamoxifen in estrogen-receptor positive, node-negative breast cancer patients using a cross-validated support vector machine (SVM). The algorithm was predictive on blind-test data (p = 4.92 x 10-6, log-rank test). Methods developed have been made available within a web application (TMA Navigator) and an R package (rTMA). TMA Navigator produces visual data summaries, networks and survival analysis for uploaded tissue microarray (TMA) scores. rTMA expands on TMA Navigator capabilities for advanced workflows within a programming environment.
7

A computational model of reasoning from the clinical literature /

Rennels, Glenn D. January 1900 (has links)
Thesis (Ph. D.)--Stanford University, 1986. / Cover title. "June 1986." Includes bibliographical references.
8

Customized Health Information System

Burton, Arthur Powell, 1941- January 1972 (has links)
No description available.
9

Modeling and control of genetic regulatory networks

Pal, Ranadip 15 May 2009 (has links)
No description available.
10

Modeling and control of genetic regulatory networks

Pal, Ranadip 15 May 2009 (has links)
No description available.

Page generated in 0.0816 seconds