Badih GHATTAS - Activités de recherche

B. GHATTAS

Forethcoming...

  1. F. Combes, R. Fraiman, B. Ghattas, Subsampling Optimisation. Submitted, 2021.
  2. D. Obst, B. Ghattas, S. Claudel, J. Cugliari, Y. Goude, G. Oppenheim, Textual Data for Time Series Forecasting . Submitted, 2021.
  3. J. Fournel, B. Ghattas, A. Le Troter, D. Bendahan, ``Segmentation of individual muscles in MR images using Convolutional Neural Networks can be improved using Muscles and Borders parcellations''. Submitted, 2021.
  4. M. Bourel, B. Ghattas, M. Gonzalez. ``Comparing partitions through the Matching Error''. Submitted, 2021.

Theoretical and technical papers

  1. D. Obst, B. Ghattas, S. Claudel, J. Cugliari, Y. Goude, G. Oppenheim, Transfer learning for Linear Regression: a statistical test of gain. To appear in CSDA, 2022.
  2. A. Bartoli, J. Fournel, L. Ait-Yahia, F. Cadour, F. Tradi, B. Ghattas, S. Cortaredona, M. Million, A. Lasbleiz, A. Dutour, B. Gaborit, A. Jacquier, "Automatic deep-learning segmentation of epicardial adipose tissue from low-dose chest CT and prognosis impact on COVID-19", To appear in Cells, 2022.
  3. A. Bartoli, J. Fournel, A. Maurin, B. Marchi, P. Habert,S. Cortaredona, JC Lagier, M. Million, D. Raoult, B. Ghattas, A. Jacquier, "Value of a Deep-Learning segmentation model of COVID-19 lung lesions on low-dose chest CT", To appear in Research in Diagnostic and Interventional Imaging, 2022.
  4. B. Ghattas, A. Pinto, S. Diao, "MapReduce Clustering for Big Data", IEEE International conference on BIG Data; Machine Learning on Big Data (MLBD 2021).
  5. G.M. de la Escalera, A. Segura, C. Kruk, B. Ghattas, F. Cohan, A. Iriarte, C. Piccini. ``Genotyping and multivariate regression trees reveal ecological diversification within the Microcystis aeruginosa complex along a wide environmental gradient''.  Applied and Environmental Microbiology, 2021.
  6. K. Jebreen, MM. Nawaf, A. Barham, B. Ghattas. Inferring linear and nonlinear Interaction networks using neighborhood support vector machines. In press, ICEET, 2021
  7. Fratani, A. and Viseur, S. and Popineau, F. and Henry, P. and Ghattas, B. and Oppenheim, G. and Dhont, D. and Gout, C. "Ranking Geological Cross-Sections for database querying". Research for Integrative Numerical Geology , 2021.
  8. J. Fournel, A. Bartoli, D.Bendahan, M. Guy, M. Bernard, E. Rause, M. Y.Khanjif, S.E. Petersen, A. Jacquier, B. Ghattas. Medical image segmentation automatic quality control: A multi-dimensional approach.In press, Medical Image Analysis, 2021
  9. A. Benoit, B. Ghattas, E. Amri, J. Fournel and P. Lambert. « Deep learning for semantic segmentation » In Multi-faceted Deep Learning: Models and Data, Chapter 3, Springer, 2021.
  10. A. Cholaquidis, R. Fraiman, B. Ghattas, J. Kalemkerian. ``A combined strategy for multivariate density estimation''. In press, Journal of Non Parametric Statistics, 2021.
  11. A. Bartoli, J. Fournel, Z. Bentatou, G. Habib, A. Lalande, M. Bernard, L. Boussel, F. Pontana, J. Ndacher, B. Ghattas, A. Jacquier, "Deep Learning-Based Automated Segmentation of the Left Ventricular Trabeculations and Myocardium on Cardiac Magnetic Resonance Images: a Feasibility Study", Radiology Artificial Intelligence, 2020.
  12. Q. Ferré, G. Charbonnier, N. Sadouni, F. Lopez, Y. Kermezli, S. Spicuglia, C. Capponi, B. Ghattas, D. Puthier. "OLOGRAM : Determining significance of overlap length between genomic regions sets", Bioinformatics, Volume 36, Issue 6, Pages 1920–1922, 15 March 2020.
  13. L. Boyer, B.Ghattas, "Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database". Medecine, Vol.99 (49),2020.
  14. J. Fournel, A. Le Troter, S. Guis, D. Bendahan, B. Ghattas. "A fully convolutional neural network-based segmentation of individual muscles in MR images using muscles and borders parcellations". Annals of the Rheumatic Diseases, 2019; 78:2034.
  15. C. Aaron, A. Cholaquidis, R. Fraiman, B. Ghattas. ``Multivariate and functional robust fusion methods for structured Big Data''. JMVA, Volume 170, Pages 149-161, 2019.
  16. B. Ghattas, P. Michel, L. Boyer «Assessing variable importance in clustering: A new method based on unsupervised binary decision trees». Comput. Statistics, 34, pages 301–321, 2019.
  17. Michel P, Hamidou Z, Baumstarck K, Ghattas B, Resseguier N, Chinot O, Barlesi F, Salas S, Boyer L, Auquier P. Clustering based on unsupervised binary trees to define subgroups of cancer patients according to symptom severity in cancer. Qual Life Res. 2018 Feb;27(2):555-565. doi: 10.1007/s11136-017-1760-9. Epub 2017 Dec 8. PMID: 29218507.
  18. C. Crisci, R. Terra, JP. Pacheco, B. Ghattas, M. Bidegain, G. Goyenola, JJ. Lagomarsino, G. Méndez, N. Mazze. «Multi-model approach to predict phytoplankton biomass and composition dynamics in a eutrophic shallow lake governed by extreme meteorological events» Ecological Modelling, 360C, pp80-93, 2017.
  19. B. Ghattas, K. Jebreen «Dynamic graphical model for non linear time series», Proceedings of the 16th International Conference On Machine Learning And Applications (ICMLA), 2017.
  20. M. Bourel, B. Ghattas «Direct Multiclass boosting using base classifiers' posterior probabilities estimates». Proceedings of the 16th International Conference On Machine Learning And Applications, ICMLA, 2017.
  21. Aaron C., Cholaquidis A., Fraiman R., Ghattas B. «Robust fusion methods for Big Data». In: Aneiros G., G. Bongiorno E., Cao R., Vieu P. (eds) Functional Statistics and Related Fields, pp 7-14. Contributions to Statistics. Springer, Cham, 2017.
  22. B. Ghattas, P. Michel, L. Boyer «Clustering nominal data using Unsupervised Binary decision Trees: Comparisons with the state of the art methods», Pattern Recognition, 2017.
  23. B. Ghattas, K. Jebreen «Bayesian Network Classification: Application to Epilepsy Type Prediction Using PET Scan Data», Proceedings of the ICMLA, Pages:965-970, 2016.
  24. P. Michel, B. Ghattas, «Variable Importance in Clustering Using Binary Decision Trees», Proceedings of Compstat 2016, pp 327-337, 22nd International Conference on Computational Statistics, 2016.
  25. B. Ghattas, P. Michel, «Clustering ordinal data using binary decision trees», Proceedings of Compstat 2014, pp. 617-624, 21st International Conference on Computational Statistics, 2014.
  26. M. Bourel, R. Fraiman, and B. Ghattas, «Random Average Shifted Histograms», Computational Statistics and Data Analysis, Vol 79, pp. 149-164, DOI information: 10.1016/j.csda.2014.05.004, 2014.
  27. M. Bourel and B. Ghattas, «Aggregating Density Estimators: An Empirical Study,» Open Journal of Statistics, Vol. 3 No. 5, pp. 344-355, 2013.
  28. M. Boutahar, B. Ghattas, D. Pommeret, «Nonparametric comparison of several transformations of distribution functions», Journal of Non Parametric Statistics, Volume 25, Issue 3, September 2013, pages 619-633, 2013.
  29. R. Fraiman, B. Ghattas and M. Svarc «Interpretable Clustering using Unsupervised Binary Trees», Advances of Data Analysis and Classification, Vol 7 (2), pp 125-145, 2013. R package home page.
  30. B. Ghattas, C. Deniau «Multivariate unsupervised discretization preserving mutual information», Advances and Applications in Statistics,Volume 19, Issue 1, Pages 49 - 64, November 2010.
  31. B. Ghattas, D. Pommeret, L. Reboul, A.F. Yao. «Smooth test for paired populations», Journal of Statistical Planning and Inference, 141, pp. 262-275, 2010.

Applications

  1. P. Michel, B. Ghattas, L. Boyer, ``Computerized adaptive testing with Decision Regression Trees: an alternative to Item Response Theory for Quality of Life measurement in Multiple Sclerosis'', Patient Preference and Adherence , 2018; 12: 1043–1053.
  2. Pierre Michel, Karine Baumstarck, Christophe Lançon, Badih Ghattas, Anderson Loundou, Pascal Auquier et Laurent Boyer «Modernizing quality of life assessment: development of a multidimensional computerized adaptive questionnaire for patients with schizophrenia",  Quality of life Research, 2018 Apr;27(4):1041-1054.
  3. P. Michel, K. Baumstarck, B. Ghattas, J. Pelletier, A. Loundou, M. Boucekine, P. Auquier, L. Boyer. « A multidimensional computerized adaptive short-form quality of life questionnaire developed and validated for multiple sclerosis: the MusiQoL-MCAT ». Medecine, 95(14):e3068, 2016.
  4. M. Koob, N. Girard, B. Ghattas, S. Fellah, S. Confort-Gouny, D. Figarella-Branger, D. Scavarda. «The diagnostic accuracy of multiparametric MRI to determine pediatric brain tumor grades and types », J Neurooncol. 2016 Apr;127(2):345-53. doi: 10.1007/s11060-015-2042-4.
  5. E. Lareau-Trudel, A. Le Troter, B. Ghattas, J. Pouget, S. Attarian, D. Bendahan, E. Salort-Campana. "Muscle quantitative MR imaging and clustering analysis in patients with Facioscapulohumeral muscular dystrophy type 1". To appear in PLOS ONE, 2015, 10(7): e0132717. doi:10.1371/journal.pone.0132717..
  6. P. Michel, P. Auquier, K. Baumstarck, A. Loundou, B. Ghattas, C. Lancon, L. Boyer. "How to interpret multidimensional quality of life questionnaires for patients with schizophrenia?. Quality of Life Research, 24(10), 2015.
  7. P. Michel, P. Auquier, K. Baumstarck, J. Pelletier, A. Loundou, B. Ghattas, L. Boyer. "Development of a cross-cultural item bank for measuring quality of life related to mental health in multiple sclerosis patients". Qual Life Res., 24(9), 2015.
  8. M. Boucekine, L. Boyer, K. Baumstarck, A. Millier, B. Ghattas, P. Auquier, M. Toumi. "Exploring the response shift effect on the quality of life of patients with schizophrenia: an application of the Random Forest method", Medical Decision Making, 2015, Apr.
  9. J. Wegrzyk, A. Fouré, N.A. Maffiuletti, C. Vilmen, JP. Mattei, B. Ghattas, N. Place, D. Bendahan, J. Gondin. "Extra Forces induced by wide-pulse, high-frequency electrical stimulation: Occurrence, magnitude, variability and underlying mechanisms". Clinical Neurophysiology, 2015 July.
  10. B. Ghattas, A. Dixneuf, "Using the strain-counterstrain approach to highlight the body unity within the osteopathic treatment", The American Academy of Osteopathy Journal, November 2014, Vol 24, N3, pp 23-34.
  11. Michel, P.; Baumstarck, K.; Boyer, L.; Fernandez, O.; Flachenecker, P.; Pelletier, J.; Loundou, A.; Ghattas, B.; Auquier, P. "Defining Quality of Life Levels to Enhance Clinical Interpretation in Multiple Sclerosis: Application of a Novel Clustering Method.", Medical Care, 2017 Jan;55(1):e1-e8. doi: 10.1097/MLR.0000000000000117. PMID: 24638117.
  12. L. Boyer, K. Baumstarck, P. Michel, M. Boucekine, A. Anota, F. Bonnetain, J. Coste, B. Falissard, A. Guilleux, J.B. Hardouin, A. Loundou, M. Mercier, M. Mesbah, A. Rouquette, V. Sebille, M. Verdam, B. Ghattas, F. Guillemin, P. Auquier. "Statistical challenges of quality of life and cancer: New avenues for future research", Expert Review of Pharmacoeconomics & Outcomes Research ,2014 Feb;14(1):19-22.
  13. M. Boucekine, A. Loundou, K. Baumstarck, P. Minaya-Flores, J. Pelletier, B. Ghattas and P. Auquier. "Using the random forest method to detect a response shift in the quality of life of multiple sclerosis patients: a cohort study". BMC Medical Research Methodology, pp 13:20, 2013.
  14. Fellah S, Caudal D, De Paula AM, Dory-Lautrec P, Figarella-Branger D, Chinot O, Metellus P, Cozzone PJ, Confort-Gouny S, Ghattas B, Callot V, Girard N., "Multimodal MR Imaging (Diffusion, Perfusion, and Spectroscopy): Is It Possible To Distinguish Oligodendroglial Tumor Grade and 1p/19q Codeletion in the Pretherapeutic Diagnosis? ". Am. J. of Neuroradiology,, 2013 Jul;34(7):1326-33.
  15. B. Ghattas, C. Crisci, G. Perera, "A review of machine Learning algorithms and their application to ecological data", Ecological Modeling,240, (2012) pp.113-122.

Publications dans des revues avec "referees" jusqu'en 2008

  1. B. Ghattas, A. Ben Ishak, " Sélection de variables en classification binaire : comparaisons et application aux données de biopuces", Journal de la Société Française de Statistique, vol.149, N°3, pp43-66, 2008.
  2. M. Pons, S. Marroni, I. Machado, B. Ghattas and A. Domingo, "Machine Learning procedures: An application to bycatch data of the marine turtles Caretta-Caretta", Statistical Bulletin of ICCAT, N°038; 2008.
  3. B. Ghattas, D. Nerini, "Classifying densities using functional regression trees: Applications in oceanology". Computational Statistics & Data Analysis Volume 51, Issue 10, Pages 4984-4993, 2007.
  4. B. Ghattas, G. Perera, "From elementary martingale calculus to mixtures of experts", Boletín de la Asociacion Matemática Venezolana. Vol. XIII, N°2, pp 129-154, 2006.
  5. Fabrice Lopez, Samuel Granjeaud, Takeshi Ara, Badih Ghattas, Daniel Gautheret."The Disparate Nature of Intergenic Polyadenylation Sites", RNA, 12:(10), 1794-1801, Oct 2006.
  6. D. Brion, J.-C. Calvet, P. Le moigne, B. Ghattas, F. Habets, "Reconstitution par arbres de régression du rayonnement visible descendant horaire sur la France continentale, à partir de données in situ et de simulations: Spatialisation et vérification sur des données indépendantes" . Note N°82 du Centre National de Recherches Météorologiques, Décembre 2005.
  7. D. Martin, B. Ghattas, D. Thieffry, "Prédire la transcription à partir des séquences génomiques". Médecine/Science 20: 1036-40, 2004.
  8. Bendahan D, Guis S, Monnier N, Kozak-Ribbens G, Lunardi J, Ghattas B, Mattei JP, Cozzone PJ., "Comparative analysis of in vitro contracture tests with ryanodine and a combination of ryanodine with either halothane or caffeine: a comparative investigation in malignant hyperthermia. Acta Anaesthesiol Scand., 48(8):1019-27, 2004.
  9. M. Roussel, J.P. Mattei, Y. Le Fur, B. Ghattas, P.J. Cozzone, D. Bendahan, "Metabolic determinants of the onset of acidosis in exercising human muscle: a 31P MRS study". Journal of Applied Physiology 94(3):1145-52, 2003.
  10. D. Bendahan, J.P. Mattei, B. Ghattas, S. Confort-Gouny, M.E. Leguern, P.J. Cozzone, "Citrulline/malate promotes aerobic energy production in human exercising muscle". British Journal of Sports Medecine, 36(4):282-9, 2002.
  11. D. Bendahan, G. Kozak-Ribbens, S. Confort-Gouny, B. Ghattas, D. Figarella-Branger, M. Aubert, P.J. Cozzone, "A noninvasive investigation of muscle energetics supports similarities between exertional heat stroke and malignant hyperthermia". Anesthesia and Analgesia, Volume 93, Issue 3, Pages 683-689, 2001.
  12. B. Ghattas, L. Mary, P. Renzy, D. Robin, " Prévision de l'ozone dans l'Aire Métropolitaine Marseillaise, par des méthodes non paramétriques", Pollution Atmosphérique, 2000.
  13. D. Nerini, J.P. Durbec, C. Mante, F. Garcia, B. Ghattas, "Forecasting physicochemical variables by a classification tree method. Application to the Berre lagoon ", Acta Biologica, pp. 29-39, 2000.
  14. B. Ghattas, "Agrégation d'arbres de classifications", Revue de Statistique Appliquée, Vol. XLVIII (2), pp. 85-98, 2000.
  15. B. Ghattas, "Importance des variables dans les méthodes CART ", Modulad, N°24, pp. 29-39, Décembre 1999.
  16. B. Ghattas, "Procédure manuelle de construction d'arbres de régression ", Modulad, N°24, pp. 17-28, Décembre 1999.
  17. B. Ghattas, "Méthodes non paramétriques pour la prévision de l'ozone " OCEANIS, N°24 (1), 1999.
  18. B. Ghattas, "Prévision par arbre de classification ", Mathématiques Informatique et Sciences Humaines, N°142, pp. 31-49, 1999.
  19. B. Ghattas, "Prévision des pics d'ozone par arbres simples et agrégés par bootstrap ", Revue de Statistique Appliquée, Vol. XLVII (2), pp. 61-80, 1999.
  20. L.Bel, L.Bellanger, V.Bonneau, G.Ciuperca, D.Dacunha-Castelle, C.Deniau, B. Ghattas, M.Misiti, G.Oppenheim, J.M.Poggi, R.Tomassone, "Eléments de comparaison de prévisions statistiques des pics d'ozone" Revue de Statistique Appliquée. Vol. XLVII (3), 7-25, 1999.