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Search Results: 1 - 10 of 227485 matches for " Amir R Razavi "
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Non-compliance with a postmastectomy radiotherapy guideline: Decision tree and cause analysis
Amir R Razavi, Hans Gill, Hans ?hlfeldt, Nosrat Shahsavar
BMC Medical Informatics and Decision Making , 2008, DOI: 10.1186/1472-6947-8-41
Abstract: Analysis of 759 patients with malignant breast cancer using decision tree induction (DTI) found patterns of non-compliance with the guideline. The PMRT guideline was used to separate cases according to the recommendation to receive or not receive PMRT. The two groups of patients were analyzed separately. Resulting patterns were transformed into rules that were then compared with the reasons that were extracted by manual inspection of records for the non-compliant cases.Analyzing patients in the group who should receive PMRT according to the guideline did not result in a robust decision tree. However, classification of the other group, patients who should not receive PMRT treatment according to the guideline, resulted in a tree with nine leaves and three of them were representing non-compliance with the guideline. In a comparison between rules resulting from these three non-compliant patterns and manual inspection of patient records, the following was found:In the decision tree, presence of perigland growth is the most important variable followed by number of malignantly invaded lymph nodes and level of Progesterone receptor. DNA index, age, size of the tumor and level of Estrogen receptor are also involved but with less importance. From manual inspection of the cases, the most frequent pattern for non-compliance is age above the threshold followed by near cut-off values for risk factors and unknown reasons.Comparison of patterns of non-compliance acquired from data mining and manual inspection of patient records demonstrates that not all of the non-compliances are repetitive or important. There are some overlaps between important variables acquired from manual inspection of patient records and data mining but they are not identical. Data mining can highlight non-compliance patterns valuable for guideline authors and for medical audit. Improving guidelines by using feedback from data mining can improve the quality of care in oncology.Recurrence of breast cancer is a
Exploring cancer register data to find risk factors for recurrence of breast cancer – application of Canonical Correlation Analysis
Amir R Razavi, Hans Gill, Olle St?l, Marie Sundquist, Sten Thorstenson, Hans ?hlfeldt, Nosrat Shahsavar, the South-East Swedish Breast Cancer Study Group
BMC Medical Informatics and Decision Making , 2005, DOI: 10.1186/1472-6947-5-29
Abstract: One essential outcome after breast cancer treatment is recurrence of the disease. It is important to understand the relationship between different predictors and recurrence, including the time interval until recurrence. This study describes the application of CCA to find important predictors for two different outcomes for breast cancer patients, loco-regional recurrence and occurrence of distant metastasis and to decrease the number of variables in the sets of predictors and outcomes without decreasing the predictive strength of the model.Data for 637 malignant breast cancer patients admitted in the south-east region of Sweden were analyzed. By using CCA and looking at the structure coefficients (loadings), relationships between tumor specifications and the two outcomes during different time intervals were analyzed and a correlation model was built.The analysis successfully detected known predictors for breast cancer recurrence during the first two years and distant metastasis 2–4 years after diagnosis. Nottingham Histologic Grading (NHG) was the most important predictor, while age of the patient at the time of diagnosis was not an important predictor.In cancer registers with high dimensionality, CCA can be used for identifying the importance of risk factors for breast cancer recurrence. This technique can result in a model ready for further processing by data mining methods through reducing the number of variables to important ones.Breast cancer is the most common type of cancer diagnosed in women in Western countries. Sweden has had a high incidence of breast cancer for several decades, although mortality rates have been lower than in most other Western countries [1].Breast cancer prognosis is influenced by many factors such as morphological and pathological tumor specifications and biological tumor markers. Studying these predictors and finding those of most importance can give clinicians better insight regarding the prognosis.As a rule, data on cancer patients h
A Context-based Trust Management Model for Pervasive Computing Systems
Negin Razavi,Amir Masoud Rahmani,Mehran Mohsenzadeh
International Journal of Computer Science and Information Security , 2009,
Abstract: Trust plays an important role in making collaborative decisions about service evaluation and service selection in pervasive computing. Context is a fundamental concept in pervasive systems, which is based on the interpretation of environment and systems. The dynamic nature of context can strongly affect trust management and service selection. In this paper, we present a context-based trust management model for pervasive computing systems. The concept of context is considered in basic components of the model such as trust computation module, recommender assessment module, transaction management module, and request responder. In order to measure a predicted trustworthiness according to the fuzzy nature of trust in pervasive environments, fuzzy concepts are integrated in the proposed model.
A Context-based Trust Management Model for Pervasive Computing Systems
Negin Razavi,Amir Masoud Rahmani,Mehran Mohsenzadeh
Computer Science , 2009,
Abstract: Trust plays an important role in making collaborative decisions about service evaluation and service selection in pervasive computing. Context is a fundamental concept in pervasive systems, which is based on the interpretation of environment and systems. The dynamic nature of context can strongly affect trust management and service selection. In this paper, we present a context-based trust management model for pervasive computing systems. The concept of context is considered in basic components of the model such as trust computation module, recommender assessment module, transaction management module, and request responder. In order to measure a predicted trustworthiness according to the fuzzy nature of trust in pervasive environments, fuzzy concepts are integrated in the proposed model.
Clustering Using Isoperimetric Number of Trees
Amir Daneshgar,Ramin Javadi,Basir Shariat Razavi
Computer Science , 2012,
Abstract: In this paper we propose a graph-based data clustering algorithm which is based on exact clustering of a minimum spanning tree in terms of a minimum isoperimetry criteria. We show that our basic clustering algorithm runs in $O(n \log n)$ and with post-processing in $O(n^2)$ (worst case) time where $n$ is the size of the data set. We also show that our generalized graph model which also allows the use of potentials at vertices can be used to extract a more detailed pack of information as the {\it outlier profile} of the data set. In this direction we show that our approach can be used to define the concept of an outlier-set in a precise way and we propose approximation algorithms for finding such sets. We also provide a comparative performance analysis of our algorithm with other related ones and we show that the new clustering algorithm (without the outlier extraction procedure) behaves quite effectively even on hard benchmarks and handmade examples.
Some characteristics of age parameter for Yakutsk array data
R Razavi,SJ Fatemi
Iranian Journal of Physics Research , 2011,
Abstract: In this paper some characteristics of age parameter(s) are studied on the basis of showers from Yakutsk array data [1] having energy ranging from 1018 eV to 1019 eV.
Enabling Cognitive Load-Aware AR with Rateless Coding on a Wearable Network
R. Razavi,M. Fleury,M. Ghanbari
Advances in Multimedia , 2008, DOI: 10.1155/2008/853816
Abstract: Augmented reality (AR) on a head-mounted display is conveniently supported by a wearable wireless network. If, in addition, the AR display is moderated to take account of the cognitive load of the wearer, then additional biosensors form part of the network. In this paper, the impact of these additional traffic sources is assessed. Rateless coding is proposed to not only protect the fragile encoded video stream from wireless noise and interference but also to reduce coding overhead. The paper proposes a block-based form of rateless channel coding in which the unit of coding is a block within a packet. The contribution of this paper is that it minimizes energy consumption by reducing the overhead from forward error correction (FEC), while error correction properties are conserved. Compared to simple packet-based rateless coding, with this form of block-based coding, data loss is reduced and energy efficiency is improved. Cross-layer organization of piggy-backed response blocks must take place in response to feedback, as detailed in the paper. Compared also to variants of its default FEC scheme, results from a Bluetooth (IEEE 802.15.1) wireless network show a consistent improvement in energy consumption, packet arrival latency, and video quality at the AR display.
Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link
R. Razavi,M. Fleury,M. Ghanbari
Advances in Multimedia , 2007, DOI: 10.1155/2007/45798
Abstract: Bluetooth's default automatic repeat request (ARQ) scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly) B-slices by inspection of packet headers without the need for encoder intervention.
Enhancement of canthaxanthin production from Dietzia natronolimnaea HS-1 in a fed-batch process using trace elements and statistical methods
Nasri Nasrabadi, M. R.;Razavi, S. H.;
Brazilian Journal of Chemical Engineering , 2010, DOI: 10.1590/S0104-66322010000400003
Abstract: under fed-batch process conditions, the statistical analysis of trace elements was performed by application of plackett-burman design (for screening tests) and response surface methodology (for predicting the optimal points) to achieve the highest level of canthaxanthin production from dietzia natronolimnaea hs-1. plackett-burman design was conducted on eleven trace elements (i. e., aluminum, boron, cobalt, copper, iron, magnesium, manganese, molybdenum, selenium, vanadium and zinc) to select out elements that significantly enhance the canthaxanthin production of d. natronolimnaea hs-1. plackett-burman design revealed that fe3+, cu2+ and zn2+ ions had the highest effect on canthaxanthin production of d. natronolimnaea hs-1 (p<0.05). these three elements were used for further optimization. by means of response surface methodology for the fed-batch process, the optimum conditions to achieve the highest level of canthaxanthin (8923±18 μg/l) were determined as follow: fe3+ 30 ppm, cu2+ 28.75 ppm and zn2+ 27 ppm.
Preparation of Chitosan from Brine Shrimp (Artemia urmiana) Cyst Shells and Effects of Different Chemical Processing Sequences on the Physicochemical and Functional Properties of the Product
Hossein Tajik,Mehran Moradi,Seyed Mehdi Razavi Rohani,Amir Mehdi Erfani,Farnood Shokouhi Sabet Jalali
Molecules , 2008, DOI: 10.3390/molecules13061263
Abstract: Chitosan (CS) was prepared from Artemia urmiana cyst shells using the same chemical process as described for the other crustacean species, with minor adjustments in the treatment conditions. The influence of modifications of the CS production process on the physiochemical and functional properties of the CS obtained was examined. The study results indicate that Artemia urmiana cyst shells are a rich source of chitin as 29.3-34.5% of the shell’s dry weight consisted of this material. Compared to crab CS (selected as an example of CS from a different crustacean source) Artemia CS exhibited a medium molecular weight (4.5-5.7 ×105 Da), lower degree of deacetylation (67-74%) and lower viscosity (29-91 centiposes). The physicochemical characteristics (e.g., ash, nitrogen and molecular weight) and functional properties (e.g., water binding capacity and antibacterial activity) of the prepared Artemia CSs were enhanced, compared to control and commercial samples, by varying the processing step sequence.
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