Vine copula and artificial neural network models to analyze breast cancer data

Date

2021-02-01

Author

Farnoudkia, Hajar
Purutçuoğlu Gazi, Vilda

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

81
views

0
downloads

URI

https://www.degruyter.com/document/doi/10.1515/9783110668322/html
https://hdl.handle.net/11511/98902

Relation

Artificial Intelligence for Data-Driven Medical Diagnosis

Collections

Department of Statistics, Book / Book chapter

Suggestions

OpenMETU
Core

Vine copula graphical models in the construction of biological networks Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda (2021-01-01) The copula Gaussian graphical model (CGGM) is one of the major mathematical models for high dimensional biological networks which provides a graphical representation, espe-cially, for sparse networks. Basically, this model uses a regression of the Gaussian graphical model (GGM) whose precision matrix describes the conditional dependence between the variables to estimate the coefficients of the linear regression model. The Bayesian inference for the model parameters is used to overcome the dimensional limita...
Vine copula graphical models in the construction of biological networks Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda (null; 2019-09-19)
Graph convolutional networks for region of interest classification in breast histopathology Aygüneş, Bulut; AKSOY, SELİM; Cinbiş, Ramazan Gökberk; KÖSEMEHMETOĞLU, KEMAL; Önder, Sevgen; Üner, Ayşegül (2020-03-16) Deep learning-based approaches have shown highly successful performance in the categorization of digitized biopsy samples. The commonly used setting in these approaches is to employ convolutional neural networks for classification of data sets consisting of images all having the same size. However, the clinical practice in breast histopathology necessitates multi-class categorization of regions of interest (ROI) in biopsy samples where these regions can have arbitrary shapes and sizes. The typical solution ...
Beam search algorithm for capacity allocation problem in flexible manufacturing systems Ozpeynirci, Selin Bilgin; Azizoğlu, Meral (Elsevier BV, 2009-05-01) This study considers the operation assignment and tool allocation problem in flexible manufacturing systems. A set of operations together with their required tools are selected so as to maximize the total weight. The machines have limited time and tool magazine capacities and the tools are available in limited quantities. We develop a beam search algorithm and obtain near optimal solutions for large size problems very quickly.
Graph-based joint channel estimation and data detection for large-scale multiuser MIMO-OFDM systems / Tekin, Şeref Yaşar; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2015) In this thesis, a graph-based soft iterative receiver for large-scale multiuser MIMO-OFDM systems is proposed that performs joint channel estimation and data detection over time-varying frequency selective channel. In an uplink scenario, factor graph structures for the transmitter of users and the receiver of base-station are presented, which provide Gaussian message passing between nodes. Instead of LLR, reliability information of symbols are used to decrease complexity of the proposed algorithm. Training ...

Citation Formats

H. Farnoudkia and V. Purutçuoğlu Gazi, Vine copula and artificial neural network models to analyze breast cancer data. 2021.