Mining Data From Hemodynamic Simulations for Generating Prediction and Explanation Models

被引：12

作者：

Bosnic, Zoran ^{[1
]}

Vracar, Petar ^{[1
]}

Radovic, Milos D. ^{[2
]}

Devedzic, Goran ^{[3
]}

Filipovic, Nenad D. ^{[3
]}

Kononenko, Igor ^{[1
]}

机构：

[1] Univ Ljubljana, Fac Comp & Informat Sci, Ljubljana 61000, Slovenia

[2] Res & Dev Ctr Bioengn BioIRC, Kragujevac, Serbia

[3] Fac Mech Engn, Kragujevac, Serbia

来源：

IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 2012年 / 16卷 / 02期

关键词：

Arterial stenosis; data mining; machine learning; medical expert system; CAROTID BIFURCATION; INDIVIDUAL CLASSIFICATIONS; BLOOD-FLOW; RELIABILITY; RULES;

D O I：

10.1109/TITB.2011.2164546

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for 1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain.

引用

页码：248 / 254

页数：7

共 50 条

[21] Mining the Web for generating thematic metadata from textual data
Huang, CC
Chuang, SL
Chien, LF
20TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, PROCEEDINGS, 2004, : 834 - 834
[22] Generating rules from data mining for collaboration moderator services
C. Palmer
J. A. Harding
R. Swarnkar
B. P. Das
R. I. M. Young
Journal of Intelligent Manufacturing, 2013, 24 : 313 - 330
[23] Generating rules from data mining for collaboration moderator services
Palmer, C.
Harding, J. A.
Swarnkar, R.
Das, B. P.
Young, R. I. M.
JOURNAL OF INTELLIGENT MANUFACTURING, 2013, 24 (02) : 313 - 330
[24] Spatial contextual classification and prediction models for mining geospatial data
Shekhar, S
Schrater, PR
Vatsavai, RR
Wu, WL
Chawla, S
IEEE TRANSACTIONS ON MULTIMEDIA, 2002, 4 (02) : 174 - 188
[25] Prediction Models Applied to Lung Cancer Using Data Mining
Sousa, Rita
Sousa, Regina
Peixoto, Hugo
Machado, Jose
INTELLIGENT DISTRIBUTED COMPUTING XV, IDC 2022, 2023, 1089 : 195 - 200
[26] Data mining meets Network Analysis: Traffic Prediction Models
Eterovic, Teo
Mrdovic, Sasa
Donko, Dzenana
Juric, Zeljko
2014 37TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2014, : 1479 - 1484
[27] Prediction of landslides using ASTER imagery and data mining models
Song, Kyo-Young
Oh, Hyun-Joo
Choi, Jaewon
Park, Inhye
Lee, Changwook
Lee, Saro
ADVANCES IN SPACE RESEARCH, 2012, 49 (05) : 978 - 993
[28] Didactic and informational explanation in simulations with multiple models
Kahn, TM
Brown, KE
Leitch, RR
ARTIFICIAL INTELLIGENCE IN EDUCATION: KNOWLEDGE AND MEDIA IN LEARNING SYSTEMS, 1997, 39 : 355 - 362
[29] Models, Explanation, Representation, and the Philosophy of Computer Simulations
Duran, Juan Manuel
PHILOSOPHY OF COMPUTING: THEMES FROM IACAP 2019, 2022, 143 : 221 - 249
[30] Generating sample data for mining and warehousing
Schiefer, J
Tjoa, AM
BIS'99: 3RD INTERNATIONAL CONFERENCE ON BUSINESS INFORMATION SYSTEMS, 1999, : 148 - 157

← 1 2 3 4 5 →