Fusing evidences from intracranial pressure data using Dempster-Shafer theory

被引：0

作者：

Conte, R. ^{[1
]}

Longo, M. ^{[1
]}

Allai-Ano, S. ^{[1
]}

Matta, V. ^{[1
]}

Velardi, E. ^{[2
]}

机构：

[1] Univ Salerno, Dipartimento Ingn Informaz & Ingn Elettr DIIIE, Via Ponte Melillo, Fisciano, SA, Italy

[2] Ospedale Bambino Gesu, Unita Operativa Neurotraumatologia, DEA, Rome, Italy

来源：

PROCEEDINGS OF THE 2007 15TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING | 2007年

关键词：

intracranial pressure (ICP); Dempster-Shafer theory (DST). decision support; data fusion;

D O I：

10.1109/ICDSP.2007.4288543

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Intracranial pressure (ICP) data are used to extract some relevant features (mean value, average trend, waveform shape) from each of which a degree of confidence about the pathological, Lis opposed to physiological, state of the patient is assigned, These individual confidences are defined and successively fused fit a single global index, by exploiting Dempster-Shafer theory (DST). The approach represents a quite flexible and general framework that can be useful for supporting human decisions and, as such, has many potential medical applications.

引用

页码：159 / +

页数：2

共 50 条

[41] Dempster-Shafer Theory and Connections to Information Theory
Peri, Joseph S. J.
SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XXII, 2013, 8745
[42] An extended approach for Dempster-Shafer theory
Campos, F
Cavalcante, S
PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION, 2003, : 338 - 344
[43] Multi-scale data fusion using Dempster-Shafer evidence theory
Le Hégarat-Mascle, S
Richard, D
Ottlé, C
IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET, 2002, : 911 - 913
[44] MEASURES OF DISCORD IN THE DEMPSTER-SHAFER THEORY
RAMER, A
KLIR, G
INFORMATION SCIENCES, 1993, 67 (1-2) : 35 - 50
[45] Multi-scale data fusion using Dempster-Shafer evidence theory
Le Hégarat-Mascle, S
Richard, D
Ottlé, C
INTEGRATED COMPUTER-AIDED ENGINEERING, 2003, 10 (01) : 9 - 22
[46] Dempster-Shafer Theory and Bayesian reasoning in multisensor data fusion
Braun, JJ
SENSOR FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS IV, 2000, 4051 : 255 - 266
[47] Data Fusion of Maritime Incident Databases with Dempster-Shafer Theory
Li, Yi-Zhou
Hu, Hao
Huang, Dao-Zheng
TRANSPORTATION RESEARCH RECORD, 2014, (2426) : 27 - 32
[48] Data fusion using improved Dempster-Shafer evidence theory for vehicle detection
Zhao, Wentao
Fang, Tao
Jiang, Yan
FOURTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 1, PROCEEDINGS, 2007, : 487 - 491
[49] Fusing Heterogeneous Information for Underground Utility Map Generation Based on Dempster-Shafer Theory
Cai, Jiannan
Jeon, JungHo
Cai, Hubo
Li, Shuai
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2020, 34 (03)
[50] Dempster-Shafer theory, Bayesian theory and measure theory
Peri, JSJ
Signal Processing, Sensor Fusion, and Target Recognition XIV, 2005, 5809 : 378 - 389

← 1 2 3 4 5 →