Publications

 PAGINA PERSONALA O PUTETI ACCESA LA ADRESA

https://sites.google.com/site/smarandabelciug/

 


Carti (3)

Edituri indexate CNCSIS (3)

2014 (1)
  1. Florin Gorunescu, Smaranda Belciug, Incursiune în biostatistica, Editura Albastra, Microinformatica, Cluj-Napoca,
    ISBN 978-973—650 -302 -3, 2014.
    Comanda

2012 (1)

  • Smaranda Belciug, Marina Gorunescu, Data mining: modele predictive si de clasificare. Implementare in Matlab si Java, Editura Albastra, Microinformatica, Cluj-Napoca,
    ISBN 978-973-650-290-3, 2012.
    Comanda



2011 (1)

  • Smaranda Belciug, Machine learning techniques in Computer Aided Diagnosis, Seria Computer Science, Editura Universitaria Craiova, ISBN 978-606-14-0225-0, 2011.



Articole in extenso publicate în reviste cotate ISI Web of Science (7)

2015 (1)

  1. Smaranda Belciug, Florin Gorunescu, Improving hospital bed occupancy and resource utilization through queuing modeling and evolutionary computation, Journal of Biomedical Informatics, (ISI 2014 impact factor: 2.482), ISSN 1532-0464, vol. 53, pp. 261-269, 2015.

 

2014 (2)

        1. Smaranda Belciug, Florin Gorunescu, Error-correction learning for artificial neural networks using the Bayesian paradigm. Application to automated medical diagnosis, Journal of Biomedical Informatics, http://dx.doi.org/10.1016/j.jbi.2014.07.013 , pp. 329-337 (ISI 2014 impact factor: 2.482), ISSN 1532-0464, 2014.

 

      1. Florin Gorunescu, Smaranda Belciug,Evolutionary strategy to develop learning-based decision systems. Application to Breast Cancer and Liver Fibrosis Stadialization, Journal of Biomedical Informatics, Vol. 49, pp. 112-118 (ISI 2014 impact factor: 2.131), ISSN 1532-0464, 2014.


Citari:

  1. Stoean C., Stoean R., 2014, Support Vector Machines and Evolutionary Algorithms for Classification. Single or Together?, Springer International Publishing, Intelligent Systems Reference Library, Vol. 69., ISBN: 978-3-319-06940-1
  2. Holmes, J.H., 2014, Methods and applications of evolutionary computation in biomedicine  (Editorial),  Journal of Biomedical Informatics, 49, June 2014, 11-15.
  3. Ali, Safdar, and Abdul Majid. "Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences." Journal of Biomedical Informatics (2015).
  4. Stoean, Catalin, Ruxandra Stoean, and Adrian Sandita. "Investigation of Alternative Evolutionary Prototype Generation in Medical Classification."Symbolic and
    Numeric Algorithms for Scientific Computing (SYNASC), 2014 16th International Symposium on. IEEE, 2014.



2013 (1)

  1. Smaranda Belciug, Florin Gorunescu, A hybrid neural network/genetic algorithm system applied to the breast cancer detection and reccurence, Expert Systems, The Journal of Knowledge Engineering, (Impact factor 1.231) Willey & Blackwell, Vol 30, No.3 , 243 – 254, 2013.


Citari:

      1. Soo-Jin Kim, Jung-Woo Ha, Byoung-Tak Zhang, Bayesian evolutionary hypergraph learning for predicting cancer clinical outcomes, Journal of Biomedical Informatics, http://dx.doi.org/10.1016/j.jbi.2014.02.002, 2014.
      2. Binghuang Cai, Xian Jiang, A novel artificial neural method for biomedical prediction based on matrix pseudo-inversion, Journal of Biomedical Informatics, http://dx.doi.org/10.1016/j.jbi.2013.12.009, 18 Decembrie 2013.
      3. Stoean C., Stoean R., Support Vector Machines and Evolutionary Algorithms for Classification, Springer, 2014
      4. Annastassiou, G.A, Intelligent Mathematics: Computational Analysis, Springer, 2011.


2012 (1)

    1. Florin Gorunescu, Smaranda Belciug, Marina Gorunescu, Radu Badea, Intelligent decision-making for liver fibrosis stadialization based on tandem feature selection and evolutionary-driven neural network, Expert Systems with Applications, 39, pp. 12824-12832, 2012.


Citari:

      1. Mozaffari, A., Behzadipour, S., Kohani, M., Identifying the tool-tissue force in robotic laparoscopic surgery using neuro-evolutionary fuzzy systems and a synchronous self-learning hyper level supervisor, Applied Soft Computing, Vol. 14, Part A., 12-30, 2014
      2. Pendharkar, P.C., A maximum-margin genetic algorithm for misclassification cost minimizing feature selection problem, Expert Systems with Applications 40 (10) , pp. 3918-3925, 2013.
      3. Stoean, R., Gorunescu, F., A survey on feature ranking by means of evolutionary computation, Annals of the University of Craiova, Mathematics and Computer Science Series 40 (1) , pp. 100-105, 2013.
      4. BorisovmV., 2013, Hybridization of Intellectual Technologies for Analytical Tasks of Decision-Making Support, Journal of Computer Engineering and Informatics, ISSN:2307-0072




2011 (1)

    1. Florin Gorunescu, Marina Gorunescu, Adrian Saftoiu, Peter Vilmann, Smaranda Belciug, Competitive/Collaborative Neural Computing System for Medical Diagnosis in Pancreatic Cancer Detection, Expert Systems, The Journal of Knowledge Engineering, (Impact factor 1.231) Willey & Blackwell, Vol. 28, No.1, pp. 33 - 48, February 2011.


Citari:

      1. Rajendra Acharya, U., Ng, E.Y.K., Winitha Sree, S., Chua Kuang Chua, Chattopadhyay Subhagata, Higher order spectra analysis of breast thermograms for the automated identification of breast cancer, Expert Systems, DOI: 10.1111/j.1468-0394.2012.00654.x, 2012
      2. Soumi Chakraborty, Amitava Chatterjee, Swapan Kumar Goswami, A sparse representation based approach for recognition of power systems transients, http://dx.doi.org/10.1016/j.engappai.2014.01.009, Engineering Applications of Artificial Intelligence, 2014
      3. Soumi Chakraborty, Amitava Chatterjee, Swapan Kumar Goswami, A dual-tree wavelet transform-based approach for recognition of power system transients, Expert Systems, DOI: 10.1111/exsy.12066, 2014
      4. Serisier, S., Feugier, A., Delmotte, S., Biourge, V., German, A.J., Sensual variation in the voluntary food intake of domesticated cats (felis catus), PLoS one, Published: April 23, 2014DOI: 10.1371/journal.pone.0096071, 2014
      5. Stoean C., Stoean R., Support Vector Machines and Evolutionary Algorithms for Classification, Springer, 2014
      6. Almeida, V.G., Borba, J., Pereira, T., Pereira, H.C., Cardoso, J., Correia, C., Data mining based methodologies for cardiac risk patterns identification, BIOINFORMATICS 2013 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms , pp. 127-133, 2013.
      7. Carrera, V., Melin, P., Bravo, D., Development of an automatic method for classification of signatures in a recognition system based on modular neural networks, Studies in Computational Intelligence 451 , pp. 201-210, 2013.
      8. Saftoiu, A., Vilmann, P., Gorunescu, F., Janssen, J., Hocke, M., Larsen, M., Iglesias-Garcia, J., (...), Ciurea, T., Efficacy of an artificial neural network-based approach to endoscopic ultrasound elastography in diagnosis of focal pancreatic masses, Clinical Gastroenterology and Hepatology 10 (1) , pp. 84-90.e1, 2012.
      9. Muthanantha Murugavel, A.S., Ramakrishnan, S., Balasamy, K., Gopalakrishnan, T., Lyapunov features based EEG signal classification by multi-class SVM, Proceedings of the 2011 World Congress on Information and Communication Technologies, WICT 2011 , art. no. 6141243 , pp. 197-201, 2011.
      10. Saftoiu, A., Vilmann, P., Gorunescu, F., Janssen, J., Hocke, M., Larsen, M., Iglesias-Garcia, J., (...), Ciurea, T., Accuracy of endoscopic ultrasound elastography used for differential diagnosis of focal pancreatic masses: A multicenter study, Endoscopy 43 (7) , pp. 596-603, 2011.
      11. Annastassiou, G.A, Intelligent Mathematics: Computational Analysis, Springer, 2011.



2011 (2)

    1. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Smaranda Belciug, A statistical evaluation of neural computing approaches to predict recurrent events in breast cancer, International Journal of General Systems -, Vol. 39, No. 5, pp. 471-488 (2010 Impact Factor 0.826), Taylor & Francis, 2010.(Scopus) abstract.


Citari:

      1. Garg, L., McClean, S.,Meenan, B.J., Millard, P., 2011, Phase-type survival trees and mixed distribution survival trees for clustering patients' hospital length of stay, Informatica , 22(1), 57-72, ISSN: 0868-4952

 

    1. Dan Ionut Gheonea, Adrian Saftoiu, Tudorel Ciurea, Florin Gorunescu, Sevastita Iordache, Gabriel Lucian Popescu, Smaranda Belciug, Marina Gorunescu, Larisa Sandulescu, Real-time sono-elastography in the diagnosis of diffuse liver diseases, World Journal of Gastroenterology, 2010 April 14, 16(14): 1720-1726I, SSN 1007-9327, (Impact factor 2.081), 2010. (Scopus)


Citari:

      1. Sandulescu, L., Rogoveanu, I., Gheonea, I.A., Cazacu, S., Saftoiu, A., Real-time elastography applications in liver pathology between expectations and results, Journal of Gastrointestinal and Liver Diseases 22 (2) , pp. 221-227, 2013.
      2. Ling, W.-W., Lu, Q., Ma, L., Quan, J.-R., Yang, L.-L., Luo, Y., The Methodology and influential factors of Real-time elastography in liver examination, Journal of Sichuan University (Medical Science Edition) 44 (2) , pp. 295-299, 2013.
      3. Hernandez-Andrade, E., Hassan, S.S., Ahn, H., Korzeniewski, S.J., Yeo, L., Chaiworapongsa, T., Romero, R., Evaluation of cervical stiffness during pregnancy using semiquantitative ultrasound elastography, Ultrasound in Obstetrics and Gynecology 41 (2) , pp. 152-161, 2013.
      4. Bhargava, S., Bhargava, S.K., Sharma, S., Prakash, M., Elastography: A new imaging technique and its application, Journal International Medical Sciences Academy 26 (1) , pp. 25-30, 2013.
      5. Li, Y.-Y., Su, X.-J., Wang, X.-M., Wang, S.-W., Semi-quantitative analysis of liver fibrosis in rat models with real-time ultrasonic elastography, Chinese Journal of Medical Imaging Technology 28 (7) , pp. 1259-1262, 2012.
      6. Saftoiu, A., Vilmann, P., Gorunescu, F., Janssen, J., Hocke, M., Larsen, M., Iglesias-Garcia, J., (...), Ciurea, T., Efficacy of an artificial neural network-based approach to endoscopic ultrasound elastography in diagnosis of focal pancreatic masses, Clinical Gastroenterology and Hepatology 10 (1) , pp. 84-90.e1, 2012.
      7. Bachmann-Nielsen, M., Sftoiu, A., Elastografie - richtig oder falsch? | [Elastography - True or False?], Ultraschall in der Medizin 32 (1) , pp. 5-7, 2011.
      8. Gradinaru-Tascau, O., Sporea, I., Bota, S., Jurchis, A., Popescu, A., Popescu, M., Sirli, R., Szilaski, M., Does experience play a role in the ability to perform liver stiffness measurements by means of supersonic shear imaging SSI), Med. Ulstron., Vol 15, no 3., 180-183, 2013, (PubMed)
      9. Sporea, I., Popescu A., Real-time elastography (RT-E), Hepatic Elastography Using Ultrasound Waves, 85-95, 2012, (PubMed)
      10. Salvatore, V., 2011, Changes in tumor stiffness for early prediction of tumor response to sorafenib: a proof-of-concept study with elastosonography in an animal model of Hepatocellular Carcinoma (HCC), Tesi di Dottorato dell'Alma Mater Studiorum - Università di Bologna
      11. O’tega, A.E., 2012, Optical/acoustic radiation imaging (OARI) probe developed for epithelial cancer detection, Doctoral dissertation, the George Washington University.
      12. Paparo, F., Cevasco, L., Zefiro, D., Biscaldi, E., Bacigalupo, L., Balocco, M., et al., 2013, Diagnostic value of real-time elastography in the assessment of hepatic fibrosis in patients with liver iron overload, European journal of radiology, ISSN:0938-7994, 82(12), e755-e761.
      13. Sangwaiya, M. J., Sherman, D. I., Lomas, D. J., Shorvon, P. J., 2013, Latest developments in the imaging of fibrotic liver disease. Acta Radiologica, ISSN: 0284-1851, Published online, doi:10.1177/0284185113510159, in press

 

Articole in extenso publicate în reviste indexate în baze de date internationale (4)


2014 (1)

    1. Smaranda Belciug, Florin Gorunescu, Bayesian-driven Multi-layer Perceptron Applied to Liver Fibrosis Stadialization, Egyptian Computer Science Journal, vol. 38, nr. 3, pp. 33-42, (ACM), 2014.


2013 (1)

    1. Smaranda Belciug, Florin Gorunescu, Mircea-Sebastian Serbanescu, Improving MLP classification accuracy for breast cancer detection through evolutionary computation, partially connectivity and feature selection, Egyptian Computer Science Journal, (ACM), ISSN - 1110-2586, Vol. 37, No.5, September 2013


2010 (2)

    1. Smaranda Belciug, A statistical comparison between an unsupervised neural network and a partially connected neural network in the detection of breast cancer, Annals of the University of Craiova, Mathematics and Computer Science, Science Series, Vol 37, No. 3, pp. 71-77, 2010.

 

    1. Smaranda Belciug, A two-stage decision model for breast cancer detection, Annals of the University of Craiova, Mathematics and Computer Science, Science Series, Vol37, No. 2, pp. 27-37, 2010


2008 (1)

    1. Florin Gorunescu, Marina Gorunescu, Smaranda (Gorunescu) Belciug, Adrian Saftoiu, Peter Vilmann, Application in Non-invasive Cancer Detection, Case Studies in Business, Industry and Government Statistics, (CSBIGS - USA), Vol. 2, No. 2, pp. 38-46, 2008

      Citari:
      1. ashkari, A., Full automatic micro calcification detection in mammogram images using artificial neural network and Gabor wavelets, Proceedings of the 6th IEEE Machine Vision and Image Processing, 1-7, 2010.
      2. Annastassiou, G.A, Intelligent Mathematics: Computational Analysis, Springer, 2011.

 

Articole in extenso publicate în reviste indexate CNCSIS (3)


2009 (2)

    1. Smaranda Belciug, Patients length of stay grouping using the hierarchical clustering algorithm, The 9th International Conference on Artificial Intelligence and Digital Communications, Craiova September, Annals of the University of Craiova, Mathematics and Computer Science Series, ISSN 1223-6934,Vol 36, No 2, pp. 79-84, 2009. 

 

    1. Smaranda Belciug, Monica Lupsor, A multi-layer based procedure for detecting liver fibrosis, Annals of the University of Craiova, Mathematics and Computer Science Series, ISSN 1223-6934, Vol. 36, No. 1,pp. 64-70, 2009.



2008 (1)

    1. Smaranda Belciug, Monica Lupsor, Radu Badea, Features selection approach for non-invasive evaluation of liver fibrosis, Annals of the University of Craiova, Mathematics and Computer Science Series, ISSN 1223-6934 , Vol. 35, pp. 15 - 28, 2008. 


Citari:

      1. Stoean R., Stoean C., Lupsor M., Stefanescu H., Badea R., Evolutionary conditional rules versus support vector machines weighted formulas for liver fibrosis degree prediction, Annals of the University of Craiova - Mathematics and Computer Science Series, Vol. 37, No. 1, pp. 43-54, 2010.

Articole in extenso publicate în volumele unor manifestari stiintifice internationale de tip Proceedings

Volumele unor manifestari stiintifice înternationale IEEE, cotate ISI Web of Science (7)


2010 (4)

  1. Smaranda Belciug, Florin Gorunescu, Marina Gorunescu, Abdel-Badeeh Salem, Clustering-based approach for detecting breast cancer recurrence, 10th IEEE International Conference on Intelligent Systems Design and Applications, Cairo, pp. 533 - 538, 29 Nov - 1 Dec, 2010,
    Citari:
    1. Tomar, D., Agarwal, S., A survery on Data Mining approaches for Healthcare, International Journal of Bio-Sciene and Bio-Technology, Vol. 5, No. 5, 241-266, 2013
  2. Smaranda Belciug, Florin Gorunescu, Marina Gorunescu, Salem Abdel Badeeh, Assessing Performances of Unsupervised and Supervised Neural Networks in Breast Cancer Detection, The 7th International Conference on INFOrmatics and Systems (INFOS 2010) - 28-30 March, Advances in Data Engineering and Management (ADEM) Track, ADEM 80-87., ACS.,ISBN 978-9-7740-3396-4, 2010. (Scopus) 

  3. Citari:
    1. Gharehchopogh, F.S., Molany, M., Mokri, F.D., Using artificial neural network in diagnosis of thyroid disease: a case study., International Journal of Computational Sciences and Applications, Vol. 3, No. 4, 49-61, 2013
    2. Beg, M. M., Jain, M., 2012, an Analysis of the methods employed for Breast Cancer Diagnosis, International Journal of Research in Computer Science, ISSN: 2278 – 733X, 2, 25-29
    3. Kong, Y., & Zhao, J. , 2011, Detection Method of Micro-calcification Clusters Based on Classification and Regression Decision Tree. Energy Procedia, ISSN:1876-6102, 13, 1444-1449.
    4. Annastassiou, G.A, Intelligent Mathematics: Computational Analysis, Springer, 2011.
  4. Smaranda Belciug, Elia El-Darzi, A partially connected neural network-based approach with application to breast cancer detection and recurrence, IEEE Conference on Intelligent Systems, IS2010, 191-196, 2010, London, UK, 2010. (Scopus, DBLP) Mc Leod, P., Verma, B., Multi-cluster support vector machine classifier for the classification of suspicious areas in digital mammograms, International Journal of Computational Intelligence and Applications 10 (4) , pp. 481-494, 2011.
    1. Stoean C., Stoean R., Support Vector Machines and Evolutionary Algorithms for Classification, Springer, 2014
      Citari:
  5. Florin Gorunescu, Elia El-Darzi, Smaranda Belciug, Marina Gorunescu, Patient grouping optimization using a hybrid Self-Organizing Map and Gaussian Mixture Model for length of stay-based clustering system IEEE Conference on Intelligent Systems, IS2010, 173-178, 2010, London, UK, 2010. (Scopus, DBLP) abstract.

  6. Citari:
    1. Guzman Castillo, M., Modelling patient length of stay in public hospitals in Mexico, University of Southampton, School of Management, Doctoral Thesis, 2012
    2. Xu, M., Wong, T.C., Chin, K.S., A medical procedure-based patient grouping method for an emergency department, Applied Soft Computing, Vol. 14, Part A, 31-37, 2014
    3. Annastassiou, G.A, Intelligent Mathematics: Computational Analysis, Springer, 2011.

    2008 (1)
  7. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Smaranda Belciug (Gorunescu), A statistical evaluation of neural computing approaches to predict recurrent events in breast cancer, Proceedings 4th International IEEE, Conference on Intelligent Systems - IS08, Varna, Bulgaria 6-8.09.2008, pp. 38-43, 2008. abstract.

  8. Citari:
    1. Beg, M. M., Jain, M., 2012, an Analysis of the methods employed for Breast Cancer Diagnosis, International Journal of Research in Computer Science, ISSN: 2278 – 733X, 2, 25-29

    2005 (2)
  9. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Marius Ene, Smaranda Belciug (Gorunescu), Statistical Comparison of a Probabilistic Neural Network Approach in Hepatic Cancer Diagnosis, Proceedings IEEE International Conference on Computer as a tool- Eurocon2005, Belgrade, Serbia, pp. 237-240, IEEE Press, 2005. (Scopus) abstract.
  10. Citari:
    1. Sunay A.S., Cunedioglu U., Yilmaz B., Feasibility of probabilistic neural networks, Kohonen self-organizing maps and fuzzy clustering for source localization of ventricular focal arrhythmias from intravenous catheter measurements, Expert Systems, Vol. 26, Issue 1, pp. 70-81, 2009.
    2. Rao P.N., Devi T.U., Kaladhar D., Sridhar G., Rao A.A., A probabilistic neural network approach for protein superfamily classification, Journal of Theoretical and Applied Information Technology, 11, Vol 6, No1., pp. 101-105. 2005
    3. Rouhani M., Haghighi M.M., The diagnosis of Hepatitis Diseases by Support Vector Machines and Artificial Neural Networks, Proceedings of the Computer Science and Information Technology Spring Conference, 2009, IACSITSC'09, pp. 456-458, 2009.
    4. Rouhani M., Mansouri K., Comparison of Several ANN Architectures of the Thyroid Diseases Grades Diagnosis, International Association of Computer Science and Information Technology-Spring Conference, 2009
    5. Gorunescu F., Gorunescu M., Revett K., Ene M., A hybrid incremental /Monte Carlo searching technique for the "smoothing" parameters of probabilistic neural networks, Proceedings of the International Conference on Knowledge Engineering: principles and techniques, KEPT2007, Cluj-Napoca (Romania), June 6-8, 2007, pp. 107-113.
    6. Gorunescu, F., Benchmarking Probabilistic Neural Network Algorithms, Proceedings of the 6-th Intelligence Conference on Artificial Intelligence and Digital Communications.
  11. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Smaranda Belciug (Gorunescu), An Evolutionary Computational Approach to Probabilistic Neural Network with Application to Hepatic Cancer Diagnosis, Proceedings 18th IEEE InternationalSymposium on Computer-Based Medical Systems –IEEE CBMS 2005-Dublin, Ireland, IEEE Computer Science Press (Eds. A. Tsymbal and P. Cunningham), pp. 461-466, 2005. (Scopus, DBLP) abstract.
  12. Citari:
    1. Sivagaminathan R.H., Ramakrishnan S., A hybrid approach for feature subset selection using neural networks and ant colony optimization, Expert Systems with Applications, Vol. 33, Issue 1, pp. 49-60, 2007.
    2. Jeatrakul P., Wong K.W., Comparing the performance of different neural networks for binary classification problems, Eight International Symposium on Natural Language Processing, 2009
    3. Abarghouei A.A., Ghanizadeh A., Sinaie S., Shamsuddin S.M., A survey of Pattern Recognition Application in Cancer Diagnosis, Proceedings of the Soft Computing and Pattern Recognition, 2009, SOCPAR'09, 4-7 December, 2009, pp. 448-453., 2009
    4. Revett K., Gorunescu F., Gorunescu M., Ene M., Maglhaes S., Santos H., A machine learning approach to keystroke dynamics based user authentication, International Journal of Electronic Security and Digital Forensics, Vol. 1, No. 1, pp. 55-70, 2007.

    Volumele unor manifestari stiintifice înternationale ACM (1)


    2009 (1)
  13. Marina Gorunescu, Smaranda Belciug, Salem Abdel Badeeh, Monica Lupsor, Radu Badea, Horia Stefanescu, A machine learning-based diagnosis for liver diseases using the Fibroscan medical ultrasound technique, Proceedings 4thACM International Conference on Intelligent Computing and Information Systems ICICIS09, Cairo 18 - 22 March 2009, pp. 243-248, 2009. abstract.
  14. Volumele altor manifestari stiintifice internationale (6)


    2009 (2)
  15. Smaranda Belciug, Monica Lupsor, A competitive collaboration between machine learning techniques for hepatic fibrosis detection, 4th South East European Doctoral Student Conference (DSC 2009), 6-7 July 2009, Thessaloniki, Greece, 454-462, 2009. abstract.
  16. Florin Gorunescu, Smaranda Belciug, Marina Gorunescu, Monica Lupsor, Radu Badea, Horia Stefanescu, Radial Basis Function Network-Based Diagnosis for Liver Fibrosis Estimation, Proceeding 2nd International Conference on e-Health and Bioengineering EHB 2009, 17-18 September 2009, Iasi - Constanta, Romania, Advancements of Medical Bioengineering and Informatics (Ed. UMF. "Gr. T. Popa", Iasi, pp. 209-212, 2009 abstract.

  17. 2008 (2)
  18. Florin Gorunescu, Smaranda Belciug (Gorunescu), Marina Gorunescu, A probabilistic neural network approach in medical images analysis for cancer detection, The 2nd International Health and Social Care Modelling Conference -HSCM 2008, 18 - 20 March 2008, Portrush, Northern Ireland, UK, 2008.
  19. Smaranda Belciug, Bayesian classification vs. k-nearest neighbor classification for the non-invasive hepatic cancer detection, The 8th International Conference on Artificial Intelligence and Digital Communications, Craiova, September 2008, 108, pp. 31-35, 2008. abstract.

  20. 2005 (2)
  21. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Smaranda Belciug (Gorunescu), Kenneth Revett, Aurangzeb Khan, A Cancer Diagnosis System Based on Rough Sets and Probabilistic Neural Networks, Proceedings 1st East European Conference on Health Care Modelling and Computation-HCMC2005, Craiova, Romania (Eds. F. Gorunescu, M. Gorunescu, E. El-Darzi), Medical University Press, Craiova, 149-159, 2005. abstract.
  22. Florin Gorunescu, Marina Gorunescu, Elia El-Darzi, Marius Ene, Smaranda Belciug (Gorunescu), Performance enhancement approach for Probabilistic Neural Networks, Proceedings 1st East European Conference on Health Care Modelling and Computation, -HCMC2005, Craiova, Romania (Eds. F. Gorunescu, M. Gorunescu, E. El-Darzi), Medical University Press, Craiova, 2005. abstract.
  23. Conferinte nationale (1)


    2009 (1)
  24. Smaranda Belciug, Patients Length of Stay Grouping using K-means algorithm, First Doctoral Student Workshop in Computer Science, 22-23 May 2009, Pitesti, Romania, 2009. abstract.