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Zettervall, Hang
Publications (10 of 13) Show all publications
Rakus-Andersson, E. & Zettervall, H. (2014). Fuzzified Clustering and Point Set Continuous Approximation in Prognosticating Gastric Cancer Surgery. Paper presented at eTELEMED 2014 - The Sixth International Conference on eHealth, Telemedicine, and Social Medicine. Paper presented at eTELEMED 2014 - The Sixth International Conference on eHealth, Telemedicine, and Social Medicine. Barcelona, Spain: IARIA
Open this publication in new window or tab >>Fuzzified Clustering and Point Set Continuous Approximation in Prognosticating Gastric Cancer Surgery
2014 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

We discuss two computational techniques in the current paper. In the first part, we aim at employing FCM (fuzzy c-means) clustering to compute membership degrees of two clusters providing decisions to perform surgery or not for a testing set of 25 gastric cancer patients. The second part handles mathematical modelling of a common function approximating the information obtained from the c-means procedure. After constructing the equation of the function, we can make the decision about the surgery in the form of the surgery degree for an arbitrary gastric cancer patient. A centre, dealing with mathematical techniques concerning surgery prognoses, can quickly decide about surgery for the patient who lives in a remote place. A transmission of information among the centre and some hospitals, interested in adopting the centre services, can facilitate surgery decision-making. This trial can be treated as a contribution in the telemedicine domain.

Place, publisher, year, edition, pages
Barcelona, Spain: IARIA, 2014
Keywords
c-means clustering, surgery degrees, clinical characteristic value, weights of importance, truncated π-functions.
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-6705 (URN)oai:bth.se:forskinfo38A08D8B5CAF3A84C1257CC2004717B2 (Local ID)978-1-61208-327-8 (ISBN)oai:bth.se:forskinfo38A08D8B5CAF3A84C1257CC2004717B2 (Archive number)oai:bth.se:forskinfo38A08D8B5CAF3A84C1257CC2004717B2 (OAI)
Conference
eTELEMED 2014 - The Sixth International Conference on eHealth, Telemedicine, and Social Medicine
Available from: 2014-04-23 Created: 2014-04-22 Last updated: 2016-09-20Bibliographically approved
Zettervall, H. (2014). Fuzzy Set Theory Applied to Make Medical Prognoses for Cancer Patients. (Doctoral dissertation). Karlskrona: Blekinge Institute of Technology
Open this publication in new window or tab >>Fuzzy Set Theory Applied to Make Medical Prognoses for Cancer Patients
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

As we all know the classical set theory has a deep-rooted influence in the traditional mathematics. According to the two-valued logic, an element can belong to a set or cannot. In the former case, the element’s membership degree will be assigned to one, whereas in the latter case it takes the zero value. With other words, a feeling of imprecision or fuzziness in the two-valued logic does not exist. With the rapid development of science and technology, more and more scientists have gradually come to realize the vital importance of the multi-valued logic. Thus, in 1965, Professor Lotfi A. Zadeh from Berkeley University put forward the concept of a fuzzy set. In less than 60 years, people became more and more familiar with fuzzy set theory. The theory of fuzzy sets has been turned to be a favor applied to many fields. The study aims to apply some classical and extensional methods of fuzzy set theory in life expectancy and treatment prognoses for cancer patients. The research is based on real-life problems encountered in clinical works by physicians. From the introductory items of the fuzzy set theory to the medical applications, a collection of detailed analysis of fuzzy set theory and its extensions are presented in the thesis. Concretely speaking, the Mamdani fuzzy control systems and the Sugeno controller have been applied to predict the survival length of gastric cancer patients. In order to keep the gastric cancer patients, already examined, away from the unnecessary suffering from surgical operation, the fuzzy c-means clustering analysis has been adopted to investigate the possibilities for operation contra to nonoperation. Furthermore, the approach of point set approximation has been adopted to estimate the operation possibilities against to nonoperation for an arbitrary gastric cancer patient. In addition, in the domain of multi-expert decision-making, the probabilistic model, the model of 2-tuple linguistic representations and the hesitant fuzzy linguistic term sets (HFLTS) have been utilized to select the most consensual treatment scheme(s) for two separate prostate cancer patients. The obtained results have supplied the physicians with reliable and helpful information. Therefore, the research work can be seen as the mathematical complements to the physicians’ queries.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Institute of Technology, 2014. p. 168
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 1
Keywords
Fuzzy set theory, the Mamdani fuzzy control system, the Sugeno controller, fuzzy c-means clustering analysis, point set approximation, linguistic models, the 2-tuple linguistic representations, the hesitant fuzzy linguistic term sets
National Category
Mathematics
Identifiers
urn:nbn:se:bth-00574 (URN)oai:bth.se:forskinfo60F39E5B534C2AFDC1257C390047CD27 (Local ID)978-91-7295-271-3 (ISBN)oai:bth.se:forskinfo60F39E5B534C2AFDC1257C390047CD27 (Archive number)oai:bth.se:forskinfo60F39E5B534C2AFDC1257C390047CD27 (OAI)
Available from: 2014-04-10 Created: 2013-12-06 Last updated: 2015-06-30Bibliographically approved
Zettervall, H., Rakus-Andersson, E. & Forssell, H. (2013). Applied Fuzzy C-means Clustering to Operation Evaluation for Gastric Cancer Patients. Paper presented at The Fifth International Conference on eHealth, Telemedicine, and Social Medicine - eTELEMED 2013. Paper presented at The Fifth International Conference on eHealth, Telemedicine, and Social Medicine - eTELEMED 2013. Nice, France: IARIA
Open this publication in new window or tab >>Applied Fuzzy C-means Clustering to Operation Evaluation for Gastric Cancer Patients
2013 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

Like data analysis, pattern recognition and data mining, fuzzy clustering also has been applied widely, and successful applications have been reported. In this paper we aim to employ the technique of fuzzy c-means (FCM) cluster to prognosticate the operation possibility on gastric cancer patients. Our purpose is to partition some clinical data in two fuzzy clusters. One of them considers patients who have a chance for successful surgery whereas the other cluster contains the patients without a view for surgery. Each patient is given by characteristic biological markers. The initial values of membership degrees taking place in the partition matrix are usually determined randomly. In this work we will use particularly designed membership functions to calculate the degrees of membership.

Place, publisher, year, edition, pages
Nice, France: IARIA, 2013
Keywords
Fuzzy C-means clustering analysis, Fuzzy partition, Operation decision
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-7007 (URN)oai:bth.se:forskinfo71884F5A9AEDD407C1257B2B00614E0A (Local ID)978-1-61208-252-3 (ISBN)oai:bth.se:forskinfo71884F5A9AEDD407C1257B2B00614E0A (Archive number)oai:bth.se:forskinfo71884F5A9AEDD407C1257B2B00614E0A (OAI)
Conference
The Fifth International Conference on eHealth, Telemedicine, and Social Medicine - eTELEMED 2013
Available from: 2013-03-12 Created: 2013-03-11 Last updated: 2016-09-20Bibliographically approved
Zettervall, H., Rakus-Andersson, E. & Frey, J. (2013). Applied Multi-Expert Decision Making Issue Based on Linguistic Models for Prostate Cancer Patients. In: : . Paper presented at The Fifth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies, Lisboa. IARIA
Open this publication in new window or tab >>Applied Multi-Expert Decision Making Issue Based on Linguistic Models for Prostate Cancer Patients
2013 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Abstract—In this paper, two models, one is called the probabilistic model and the other is known as the model of 2-tuple fuzzy linguistic representations, are applied to solve multi-expert decision making issues (MEDM). A MEDM problem is considered, in which a group of physicians are independently asked about assessing the effectiveness of a set of treatment therapies for a prostate cancer patient. The objective of this paper is to find the most common judgment by means of these two models. Moreover, fuzzy linguistic terms are used to express the experts’ opinions and s-parametric membership functions are designed to depict the fuzzy linguistic terms.

Place, publisher, year, edition, pages
IARIA, 2013
Keywords
multi-expert decision making, group decision making, fuzzy group decision making, linguistic modeling, linguistic choice function, 2-tuple fuzzy linguistic representation model, computing with words (CW)
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-7000 (URN)oai:bth.se:forskinfoB717E6AECE348F7DC1257B410049C7E1 (Local ID)9781612082608 (ISBN)oai:bth.se:forskinfoB717E6AECE348F7DC1257B410049C7E1 (Archive number)oai:bth.se:forskinfoB717E6AECE348F7DC1257B410049C7E1 (OAI)
Conference
The Fifth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies, Lisboa
Available from: 2013-04-04 Created: 2013-04-02 Last updated: 2016-09-30Bibliographically approved
Zettervall, H., Rakus-Andersson, E. & Forssell, H. (2013). Fuzzy C-Means Cluster Analysis and Approximated Data Strings in Operation Prognosis for Gastric Cancer Patients. In: Atanassov, Krassimir T.; Homenda, Wladyslaw; Hryniewicz, Olgierd; Kacprzyk, Janusz; Krawczak, Maciej; Nahorski, Zbigniew; Szmidt, Eulalia; Zadrozny, Slawomir (Ed.), New Trends in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics: (pp. 181-200). Warsaw: System Research Instituite, Polish Academy of Sciences
Open this publication in new window or tab >>Fuzzy C-Means Cluster Analysis and Approximated Data Strings in Operation Prognosis for Gastric Cancer Patients
2013 (English)In: New Trends in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics / [ed] Atanassov, Krassimir T.; Homenda, Wladyslaw; Hryniewicz, Olgierd; Kacprzyk, Janusz; Krawczak, Maciej; Nahorski, Zbigniew; Szmidt, Eulalia; Zadrozny, Slawomir, Warsaw: System Research Instituite, Polish Academy of Sciences , 2013, p. 181-200Chapter in book (Refereed)
Abstract [en]

The chapter is composed of two parts. In the first part we aim at employing fuzzy c-means (FCM) clustering to prognosticate membership degrees pointing out possibilities for operation and none operation for a set of 25 gastric cancer patients characterized by values of decisive biological markers. The second part handles the technique of mathematical modelling of a common membership function approximating the information collected from the given set of patients. When constructing the equation of the function we are able to determine the operation and none operation diagnosis for an arbitrary gastric cancer patient.

Place, publisher, year, edition, pages
Warsaw: System Research Instituite, Polish Academy of Sciences, 2013
Keywords
Fuzzy c-means clustering, Operation degrees for gastric cancer patients, Approximation of point sets by π-functions
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-6906 (URN)oai:bth.se:forskinfoE50DFFD6011DC61DC1257BCD00513AFC (Local ID)13 9788389475473 (ISBN)oai:bth.se:forskinfoE50DFFD6011DC61DC1257BCD00513AFC (Archive number)oai:bth.se:forskinfoE50DFFD6011DC61DC1257BCD00513AFC (OAI)
Available from: 2013-08-30 Created: 2013-08-20 Last updated: 2016-09-20Bibliographically approved
Zettervall, H., Rakus-Andersson, E. & Frey, J. (2013). Making Medication Prognoses for Prostate Cancer Patients by the Application of Linguistic Approaches. International Journal On Advances in Life Sciences, 5(3&4), 147-159
Open this publication in new window or tab >>Making Medication Prognoses for Prostate Cancer Patients by the Application of Linguistic Approaches
2013 (English)In: International Journal On Advances in Life Sciences, ISSN 1942-2660, E-ISSN 1942-2660, Vol. 5, no 3&4, p. 147-159Article in journal (Refereed) Published
Abstract [en]

Apart from the probabilistic model and the model of 2-tuple linguistic representations, a new extension of the fuzzy set, known as the hesitant fuzzy linguistic term set can be seen as the third representative of linguistic approaches. In this paper, we focus on multi-expert decision-making problems, in which a group of physicians are independently asked for assessing the effectiveness of a set of treatment therapies. Our goal is to rank the effectiveness of treatment modalities from the most recommended to the contraindicated. Two individual prostate cancer patients have been taken into account in the practical studies. For the first patient, the probabilistic model and the model of 2-tuple linguistic representations have been adopted to accomplish the medical application. Whereas, for the second patient, the approach of hesitant fuzzy linguistic term set has been used to make the medication prognoses. Moreover, the continuous fuzzy numbers in the Left-Right representations are used to mathematically express the experts’ judgments and s-parametric membership functions are designed to represent the fuzzy linguistic terms.

Place, publisher, year, edition, pages
IARIA, 2013
Keywords
Multi-expert decision making, Fuzzy group decision making, Probabilistic model, 2-tuple linguistic representations model, Hesitant fuzzy linguistic term set
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-6775 (URN)oai:bth.se:forskinfo2AD82D4CE3ACC774C1257C6F00303257 (Local ID)oai:bth.se:forskinfo2AD82D4CE3ACC774C1257C6F00303257 (Archive number)oai:bth.se:forskinfo2AD82D4CE3ACC774C1257C6F00303257 (OAI)
Available from: 2014-02-04 Created: 2014-01-29 Last updated: 2017-12-04Bibliographically approved
Zettervall, H. (2011). Fuzzy and Rough Set Theory in Treatment of Elderly Gastric Cancer Patients. (Licentiate dissertation). Karlskrona: Blekinge Institute of Technology
Open this publication in new window or tab >>Fuzzy and Rough Set Theory in Treatment of Elderly Gastric Cancer Patients
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Fuzzy set theory was presented for the first time by Professor Lotfi A. Zadeh from Berkeley University in 1965. In conventional binary logic a statement can be true or false, and there is no place for even a little uncertainty in this judgment. An element either belongs to a set or does not. We call these kinds of sets crisp sets. In practice we often experience those real situations that are represented by crisp sets as impossible to describe accurately. A two-valued logic assumes that precise symbols must be employed, and it is therefore not applicable to the real existence. If the information demanded by a system is lacking, the future state of such a system may not be known completely. One of the instruments used to handle the vagueness in the real-world situations is fuzzy set theory, which has been frequently applied in a wide range of areas like, e.g., dynamic systems, militaries, medicine and other domains. Another theory, which copes with the problem of imprecision, is known as rough set theory. It was proposed by Professor Zdzisław Pawlak in Warsaw in the 1980ties. Whereas imprecision is expressed in the category of a membership degree in fuzzy set theory, this is a matter of the set approximation in rough set theory. Due to the definition of a rough set formulated by means of the decision attribute value, two approximate sets of the rough set are determined. These contain sure and possible members of the universe considered, in which the rough set has been defined. One of the objectives of this study is to apply some classical methods of fuzzy set theory to medicine in order to estimate the survival length of gastric cancer patients. We have decided to test the action of fuzzy controllers of the Mamdani and Sugeno type. Two clinical markers, playing roles of the independent variables, have been included in the algorithm as the base information assisting the survival prognosis. Since the model results have been convergent to the expected experimental values then we will intend to make some extensions of the model concerning the larger number of independent variables. We have also utilized rough set classification, to verify the types of operations. These items are discussed in the thesis in conformity with the physicians’ wishes to support results of statistical investigations. The current research is funded by the scientific grant obtained from Blekinge Research Board.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Institute of Technology, 2011
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 3
National Category
Mathematics
Identifiers
urn:nbn:se:bth-00489 (URN)oai:bth.se:forskinfo5DE345505EA63EA5C1257838003A7B2F (Local ID)978-91-7295-202-7 (ISBN)oai:bth.se:forskinfo5DE345505EA63EA5C1257838003A7B2F (Archive number)oai:bth.se:forskinfo5DE345505EA63EA5C1257838003A7B2F (OAI)
Note
Lic. March 25thAvailable from: 2012-09-18 Created: 2011-02-15 Last updated: 2015-06-30Bibliographically approved
Rakus-Andersson, E., Zettervall, H. & Forssell, H. (2011). Fuzzy Controllers in Evaluation of Survival Length in Cancer Patients. In: Atanassov, K.; Homenda, W.; Hryniewicz, O.; Kacprzyk, J.; Krawczak, M.; Nahorski, Z.; Szmidt, E.; Zadrozny, S. (Ed.), Recent Advances in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics. Volume II: Applications (pp. 203-222). Warsaw, Poland: System Research Institute, Polish Academy of Sciences
Open this publication in new window or tab >>Fuzzy Controllers in Evaluation of Survival Length in Cancer Patients
2011 (English)In: Recent Advances in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics. Volume II: Applications / [ed] Atanassov, K.; Homenda, W.; Hryniewicz, O.; Kacprzyk, J.; Krawczak, M.; Nahorski, Z.; Szmidt, E.; Zadrozny, S., Warsaw, Poland: System Research Institute, Polish Academy of Sciences , 2011, p. 203-222Chapter in book (Refereed)
Abstract [en]

Strict analytic formulas are the tools usually derived for determining the formal relationships between a sample of independent variables and a variable which they affect. If we cannot formalize the function tying the independent and dependent variables then we will utilize some control actions. Apart from crisp versions of control we often adopt their fuzzy variants developed by Mamdani and Assilian or Sugeno. Fuzzy control algorithms are furnished with softer mechanisms, when comparing them to classical control. The algorithms are particularly adaptable to support medical systems, often handling uncertain premises and conclusions. From the medical point of view it would be desirable to prognosticate the survival length for patients suffering from gastric cancer. We thus formulate the objective of the current paper as the utilization of fuzzy control actions for the purpose of making the survival prognoses.

Place, publisher, year, edition, pages
Warsaw, Poland: System Research Institute, Polish Academy of Sciences, 2011
Keywords
Mamdani controller, Sugeno controller, Control estimation of survival length
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-7439 (URN)oai:bth.se:forskinfo2ACD5ABE547060D6C12579410063EF30 (Local ID)13 9788389475367 (ISBN)oai:bth.se:forskinfo2ACD5ABE547060D6C12579410063EF30 (Archive number)oai:bth.se:forskinfo2ACD5ABE547060D6C12579410063EF30 (OAI)
Available from: 2012-09-18 Created: 2011-11-07 Last updated: 2016-09-20Bibliographically approved
Zettervall, H., Rakus-Andersson, E. & Forssell, H. (2011). The Mamdani Controller in Prediction of the Survival Length in Elderly Gastric Patients. Paper presented at Bioinformatics. Paper presented at Bioinformatics. Rome: Springer, SciTePress
Open this publication in new window or tab >>The Mamdani Controller in Prediction of the Survival Length in Elderly Gastric Patients
2011 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

Strict analytic formulas are the tools derived for determining the formal relationships between a sample of independent variables and a variable which they affect. If we cannot formalize the function tying the independent and dependent variables then we will utilize fuzzy control actions. The algorithm is particularly adaptable to support the problem of prognosticating the survival length for gastric cancer patients. We thus formulate the objective of the current paper as the utilization of fuzzy control action for the purpose of making the survival prognoses.

Place, publisher, year, edition, pages
Rome: Springer, SciTePress, 2011
Keywords
Fuzzy control, Mamdani controller, survival length for gastric cancer patients.
National Category
Mathematics Medical and Health Sciences
Identifiers
urn:nbn:se:bth-7026 (URN)10.5220/0003134402830286 (DOI)000308455800047 ()oai:bth.se:forskinfo0EE40528893743B9C125782D0041197E (Local ID)978-989-8425-36-2 (ISBN)oai:bth.se:forskinfo0EE40528893743B9C125782D0041197E (Archive number)oai:bth.se:forskinfo0EE40528893743B9C125782D0041197E (OAI)
Conference
Bioinformatics
Available from: 2013-01-21 Created: 2011-02-04 Last updated: 2016-09-20Bibliographically approved
Rakus-Andersson, E., Zettervall, H. & Erman, M. (2010). Prioritisation of weighted strategies in multiplayer games with fuzzy entries of the payoff matrix. International Journal of General Systems, 39(3), 291-304
Open this publication in new window or tab >>Prioritisation of weighted strategies in multiplayer games with fuzzy entries of the payoff matrix
2010 (English)In: International Journal of General Systems, ISSN 0308-1079, E-ISSN 1563-5104, Vol. 39, no 3, p. 291-304Article in journal (Refereed) Published
Abstract [en]

We explore the classical model of a two-player game to select the best strategies, where action is expected to maintain the values of a certain variable on the neutral level. By inserting fuzzy sets as payoff values in the game matrix, we facilitate the procedure of formulations of payoff expectations by players. Instead of making inconvenient decisions about the choice of accurate numerical entries of the matrix, the players are able to use words, which should simplify communication between them when designing the preliminaries of the game. The players also have the possibility of making a ranking of their favourite strategies. At the next stage of the play, we involve group decision-making in order to aggregate results coming from several paired games, when more than two players contradict each other.

Place, publisher, year, edition, pages
Taylor&Francis, 2010
Keywords
two-player game, fuzzy payoff matrix, weighted strategies, group decision-making
National Category
Mathematics
Identifiers
urn:nbn:se:bth-7893 (URN)10.1080/03081070903552882 (DOI)000275196000006 ()oai:bth.se:forskinfoA575B78E12FDA721C12576B7004FEEA3 (Local ID)oai:bth.se:forskinfoA575B78E12FDA721C12576B7004FEEA3 (Archive number)oai:bth.se:forskinfoA575B78E12FDA721C12576B7004FEEA3 (OAI)
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Available from: 2012-09-18 Created: 2010-01-26 Last updated: 2018-12-19Bibliographically approved
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