The efficiency of US elastography in the differential diagnosis of thyroid nodules

Aim: To evaluate the efficiency of ultrasound elastography (USE) in the differential diagnosis of thyroid nodules. Methods: One hundred thyroid nodules in 100 patients (79 females, 21 males, age range 18-78; mean age = 45.6 years) were evaluated with real-time freehand USE, using Hitachi EUB 7500 equipment and elasticity scores were obtained. The elasticity was scored as follows: Score 1, elasticity in the entire nodule; Score 2, mainly elastic nodule with the presence of inelastic areas not constant during real time examination; Score 3, constant inelastic areas prevalently arranged at the periphery of the nodule; Score 4, constant inelastic areas prevalently arranged at the center of the nodule; Score 5, no elasticity in the nodule. Also mean strain ratio values were calculated for all nodules. Results: Eighty-four (86%) of cases were benign and sixteen (16%) were malignant. Elasticity score 3 and higher and strain ratio higher than 2.485 had statistically significant relation with malignancy (p < 0.05). Conclusions: USE including strain ratio calculations besides subjective evaluation of elasticity scores is an efficient imaging method which may contribute to the differential diagnosis of thyroid nodules

PROPER: global protein interaction network alignment through percolation matching

Background The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. Results In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. Conclusions We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch

Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting

Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods

Fuzzy time series forecasting method based on Gustafson-Kessel fuzzy clustering

Fuzzy time series approaches have being increasingly attracted researchers' attentions. The procedures on fuzzy time series actually consist of three stages; fuzzification, determination of fuzzy relations and defuzzification. Researches are generally concentrated on these stages and about improving them. In this study, we propose a new approach, which combines several techniques. In this approach, Gustafson-Kessel, which is a fuzzy clustering technique, is being used to fuzzification of time series. The proposed method is compared with the approaches in literature

THE EFFICIENCY OF ULTRASOUND ELASTOGRAPHY IN THE DIFFERENTIAL DIAGNOSIS OF THYROID NODULES

Aim: To evaluate the efficiency of ultrasound elastography (USE) in the differential diagnosis of thyroid nodules. Methods: One hundred thyroid nodules in 100 patients (79 females, 21 males, age range 18-78; mean age = 45.6 years) were evaluated with real-time freehand USE, using Hitachi EUB 7500 equipment and elasticity scores were obtained. The elasticity was scored as follows: Score 1, elasticity in the entire nodule; Score 2, mainly elastic nodule with the presence of inelastic areas not constant during real time examination; Score 3, constant inelastic areas prevalently arranged at the periphery of the nodule; Score 4, constant inelastic areas prevalently arranged at the center of the nodule; Score 5, no elasticity in the nodule. Also mean strain ratio values were calculated for all nodules. Results: Eighty-four (86\%) of cases were benign and sixteen (16\%) were malignant. Elasticity score 3 and higher and strain ratio higher than 2.485 had statistically significant relation with malignancy (p < 0.05). Conclusions: USE including strain ratio calculations besides subjective evaluation of elasticity scores is an efficient imaging method which may contribute to the differential diagnosis of thyroid nodules

ESTIMATION OF HEPATITIS C COSTS IN TURKEY VIA EXPERT OPINION: DELPHI PANEL

WOS: 00034108200019