| 1. |
- Sepehri, A. A., et al.
(författare)
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An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases
- 2016
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Ingår i: Journal of medical systems. - : Springer Science and Business Media LLC. - 0148-5598 .- 1573-689X. ; 40:1, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a robust device for automated screening of pediatric heart diseases based on our unique processing method in murmur characterization; the Arash-Band method. The present study modifies the Arash-Band method and employs output of the modified method in conjunction with the two other original techniques to extract indicative feature vectors for the screening. The extracted feature vectors are classified by using the support vector machine method. Results show that the proposed modifications significantly enhances performance of the Arash-Band in terms of the both accuracy and sensitivity as the corresponding effect sizes are sufficiently large. The proposed algorithm has been incorporated into an Android-based tablet to constitute an intelligent phonocardiogram with the automatic screening capability. In order to obtain confidence interval of the accuracy and sensitivity, an inferable statistical test is applied on our database containing the phonocardiogram signals recorded from 263 of the referrals to a hospital. The expected value of the accuracy/sensitivity is estimated to be 87.45 % / 87.29 % with a 95 % confidence interval of (80.19 % – 92.47 %) / (76.01 % – 95.78 %) exhibiting superior performance than a pediatric cardiologist who relies on conventional or even computer-assisted auscultation.
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| 2. |
- Gharehbaghi, Arash, et al.
(författare)
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A Novel Method for Screening Children with Isolated Bicuspid Aortic Valve
- 2015
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Ingår i: Cardiovascular Engineering and Technology. - : Springer Science and Business Media LLC. - 1869-408X .- 1869-4098. ; 6:4, s. 546-556
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel processing method for heart sound signal: the statistical time growing neural network (STGNN). The STGNN performs a robust classification by merging supervised and unsupervised statistical methods to overcome non-stationary behavior of the signal. By combining available preprocessing and segmentation techniques and the STGNN classifier, we build an automatic tool for screening children with isolated BAV, the congenital heart malformation which can lead to serious cardiovascular lesions. Children with BAV (22 individuals) and healthy condition (28 individuals) are subjected to the study. The performance of the STGNN is compared to that of a time growing neural network (CTGNN) and a conventional support vector (CSVM) machine, using balanced repeated random sub sampling. The average of the accuracy/sensitivity is estimated to be 87.4/86.5 for the STGNN, 81.8/83.4 for the CTGNN, and 72.9/66.8 for the CSVM. Results show that the STGNN offers better performance and provides more immunity to the background noise as compared to the CTGNN and CSVM. The method is implementable in a computer system to be employed in primary healthcare centers to improve the screening accuracy.
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| 3. |
- Gharehbaghi, Arash, et al.
(författare)
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An intelligent method for discrimination between aortic and pulmonary stenosis using phonocardiogram
- 2015
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Ingår i: IFMBE Proceedings. - Cham : Springer. - 9783319193878 ; , s. 1010-1013
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Konferensbidrag (refereegranskat)abstract
- This study presents an artificial intelligent-based method for processing phonocardiographic (PCG) signal of the patients with ejection murmur to assess the underlying pathology initiating the murmur. The method is based on our unique method for finding disease-related frequency bands in conjunction with a sophisticated statistical classifier. Children with aortic stenosis (AS), and pulmonary stenosis (PS) were the two patient groups subjected to the study, taking the healthy ones (no murmur) as the control group. PCG signals were acquired from 45 referrals to the children University hospital, comprised of 15 individuals of each group; all were diagnosed by the expert pediatric cardiologists according to the echocardiographic measurements together with the complementary tests. The accuracy of the method is evaluated to be 90% and 93.3% using the 5-fold and leave-one-out validation method, respectively. The accuracy is slightly degraded to 86.7% and 93.3% when a Gaussian noise with signal to noise ratio of 20 dB is added to the PCG signals, exhibiting an acceptable immunity against the noise. The method offered promising results to be used as a decision support system in the primary healthcare centers or clinics.
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| 4. |
- Sepehri, Amir A., et al.
(författare)
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A novel method for pediatric heart sound segmentation without using the ECG
- 2010
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 99:1, s. 43-48
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a novel method for pediatric heart sounds segmentation by paying special attention to the physiological effects of respiration on pediatric heart sounds. The segmentation is accomplished in three steps. First, the envelope of a heart sounds signal is obtained with emphasis on the first heart sound (Si) and the second heart sound (S(2)) by using short time spectral energy and autoregressive (AR) parameters of the signal. Then, the basic heart sounds are extracted taking into account the repetitive and spectral characteristics of Si and S2 sounds by using a Multi-Layer Perceptron (MLP) neural network classifier. In the final step, by considering the diastolic and systolic intervals variations due to the effect of a child's respiration, a complete and precise heart sounds end-pointing and segmentation is achieved.
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| 5. |
- Sepehri, Amir A., et al.
(författare)
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Computerized screening of children congenital heart diseases
- 2008
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Ingår i: Computerized screening of children congenital heart diseases CMPB. - United Kingdom : Elsevier BV. - 0169-2607. ; 92:2, s. 186-192
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a method for automated screening of congenital heart diseases in children through heart sound analysis techniques. Our method relies on categorizing the pathological murmurs based on the heart sections initiating them. We show that these pathelogical murmur categories can be identified by examining the heart sound energy over specific frequency bands, which we call, Arash-Bands. To specify the Arash-Band for a category, we evaluate the energy of the heart sound over all possible frequency bands. The Arash-Band is the frequency band that provides the lowest error in clustering the instances of that category against the normal ones. The energy content of the Arash-Bands for different categories constitue a feature vector that is suitable for classification using a neural network. In order to train, and to evaluate the performance of the proposed method, we use a training data-bank, as well as a test data-bank, collectively consisting of ninety samples (normal and abnormal). Our results show that in more than 94% of cases, our method correctly identifies children with congenital heart diseases. This percentage improves to 100%, when we use the Jack-Knife validation method over all the 90 samples.
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| 6. |
- Fang, Kun, et al.
(författare)
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Pairing modulations and phase separation instabilities in Bi2Sr2CaCu2O8+delta
- 2014
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Ingår i: Physics Letters A. - : Elsevier BV. - 0375-9601 .- 1873-2429. ; 378:3, s. 243-248
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Tidskriftsartikel (refereegranskat)abstract
- There is growing evidence that the unconventional spatial inhomogeneities in the doped high-T-c superconductors are accompanied by the pairing of electrons, subsequent phase transitions and condensation into coherent states. We show that such pairing states can be obtained from phase separation instabilities near level crossings. Conditions for coherent pairing instabilities are examined using exact diagonalization of Hubbard-like pyramid structures under variation of coupling and interaction strengths. We also evaluate the behavior of the energy charge gap in the vicinity of level crossings using a parametrization of coupling to the apical site to represent out-of-plane effects. These results provide a simple microscopic explanation of (correlation induced) supermodulation of the coherent pairing gap observed in scanning tunneling microscopy measurements at atomic scale in Bi2Sr2CaCu2O8+delta.
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| 7. |
- Fang, Kun, et al.
(författare)
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Possible phase separation in square and honeycomb Hubbard model : A variational cluster study
- 2015
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Ingår i: Physics Letters A. - : Elsevier BV. - 0375-9601 .- 1873-2429. ; 379:37, s. 2230-2238
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Tidskriftsartikel (refereegranskat)abstract
- The VCA ground state of the 2D Hubbard model is examined for possible phase separation under hole doping manifested by spatial inhomogeneities of coexisting different electron densities at equilibrium. Phase separation is accompanied by spectral weight loss and first Brillouin zone boundary deformation. Such an instability is observed in square structures and it is absent in honeycomb lattices. To our knowledge, no previous publications have revealed relationship between a Fermi surface instability and phase separation. Our VCA calculations provide strong support for this spontaneous instability, driven by electron correlations in specific lattice geometries, proposed in our earlier publications using exact quantum cluster calculations.
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