Badih GHATTAS - Activités de recherche



  1. D. Obst, B. Ghattas, S. Claudel, J. Cugliari, Y. Goude, G. Oppenheim, Textual Data for Time Series Forecasting . Submitted, 2023.
  2. J. Fournel, C. Lu, A. Bartoli, M. De Masi, M. Gaudry, V. Omnes, M. Guy, B. Ghattas, A. Jacquier, ``Novel risk-markers for type-B aortic dissection: are volumes more important than diameters?''. Submitted, 2023.
  3. M. Bourel, B. Ghattas, M. Gonzalez. ``A hypothesis test for comparing two partitions''. Submitted, 2023.
  4. A. Sanchez, B. Ghattas. Clustering approaches for mixed type data. Submitted, 2023.

Theoretical, technical papers and applications.

  1. N. Aung, A. Bartoli, E. Rauseo, S. Cortaredona, M. Sanghvi, J. Fournel, B. Ghattas, M. Khanji, S.E. Petersen, A. Jacquier. Association of cardiovascular risk factors with left ventricular trabeculation: Insights enabled by an AI-assisted segmentation software applied to the UK Biobank. To appear in RADIOLOGY, 2024.
  2. F. Combes, R. Fraiman, B. Ghattas, "Subsampling under distributional constraints", Statistical Analysis and Data Mining, Vol 17(1):e11661, 2024.
  3. F. Jaotombo, L. Adorni, B. Ghattas, L. Boyer, "Finding the best trade-off between performance and interpretability in predicting Hospital Length of Stay using Structured and Unstructured Data", Plos One, 18(11):1-22, 11, 2023.
  4. F. Jaotombo, V. Pauly, G. Fond, V. Orleans, P. Auquier, B. Ghattas, L. Boyer, "Machine-learning prediction for hospital length of stay using a French medico-administrative database", J Mark Access Health Policy.  , 2022 Nov 26;11(1):2149318, 26 Nov 2022.
  5. B. Ghattas, D. Manzon, "Machine Learning Alternatives to Response Surface Models". Mathematics, 11(15):3406, 2023.
  6. D. Manzon, B. Ghattas, M. Claeys-Bruno, S. Declomesnil, C. Carite, M. Sergent, "Looking for a hyper polyhedron within the multidimensional space of Design Space from the results of Designs of Experiments". Chemometrics and Intelligent Laboratory Systems, V 232, pp 104712, 2023.
  7. F. Bazangani, F. Richard, B. Ghattas, E. Guedj, « FDG-PET to T1 Weighted MRI Translation with 3D Elicit Generative Adversarial Network (E-GAN) », Sensors, 22(12), 4640, 2022.
  8. D. Obst, B. Ghattas, S. Claudel, J. Cugliari, Y. Goude, G. Oppenheim, "Transfer learning for Linear Regression: a statistical test of gain", CSDA,Vol 174, C, 2022.
  9. 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", Cells, 2022 Mar 18;11(6):1034..
  10. 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", Research in Diagnostic and Interventional Imaging, Volume 1, March 2022, 100003.
  11. 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.
  12. 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
  13. A. Cholaquidis, R. Fraiman, B. Ghattas, J. Kalemkerian. ``A combined strategy for multivariate density estimation''. In press, Journal of Non Parametric Statistics, 2021.
  14. 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.
  15. 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.
  16. F. Jaotombo, V. Pauly, P. Auquier, V. Orleans, M. Boucekine, G. Fond, B. Ghattas, L. Boyer, "Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database", Medicine  , 2020;Dec 4;99(49).
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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". PLOS ONE, 2015, 10(7): e0132717. doi:10.1371/journal.pone.0132717..
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. M. Bourel and B. Ghattas, «Aggregating Density Estimators: An Empirical Study,» Open Journal of Statistics, Vol. 3 No. 5, pp. 344-355, 2013.
  41. C. Crisci, B. Ghattas, G. Perera, "A review of machine Learning algorithms and their application to ecological data", Ecological Modeling,240, (2012) pp.113-122.
  42. B. Ghattas, C. Deniau «Multivariate unsupervised discretization preserving mutual information», Advances and Applications in Statistics,Volume 19, Issue 1, Pages 49 - 64, November 2010.
  43. 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.

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

  44. 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.
  45. 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.
  46. 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.
  47. 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.
  48. Fabrice Lopez, Samuel Granjeaud, Takeshi Ara, Badih Ghattas, Daniel Gautheret."The Disparate Nature of Intergenic Polyadenylation Sites", RNA, 12:(10), 1794-1801, Oct 2006.
  49. 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.
  50. D. Martin, B. Ghattas, D. Thieffry, "Prédire la transcription à partir des séquences génomiques". Médecine/Science 20: 1036-40, 2004.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. B. Ghattas, "Agrégation d'arbres de classifications", Revue de Statistique Appliquée, Vol. XLVIII (2), pp. 85-98, 2000.
  56. 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.
  57. 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.
  58. 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.
  59. 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.
  60. B. Ghattas, "Prévision par arbre de classification ", Mathématiques Informatique et Sciences Humaines, N°142, pp. 31-49, 1999.
  61. B. Ghattas, "Méthodes non paramétriques pour la prévision de l'ozone " OCEANIS, N°24 (1), 1999.
  62. B. Ghattas, "Procédure manuelle de construction d'arbres de régression ", Modulad, N°24, pp. 17-28, Décembre 1999.
  63. B. Ghattas, "Importance des variables dans les méthodes CART ", Modulad, N°24, pp. 29-39, Décembre 1999.
  64. Proceedings / Actes de colloques

  65. Florian Combes, Ricardo Fraiman, and Badih Ghattas.Time series sampling. Engineering Proceedings, 18(1), 2022.
  66. B. Ghattas, A. Pinto, S. Diao, "MapReduce Clustering for Big Data", IEEE International conference on BIG Data; Machine Learning on Big Data (MLBD 2021).
  67. K. Jebreen, MM. Nawaf, A. Barham, B. Ghattas. Inferring linear and nonlinear Interaction networks using neighborhood support vector machines. In press, ICEET, 2021
  68. 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.
  69. 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.
  70. 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.
  71. 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.
  72. B. Ghattas, K. Jebreen «Bayesian Network Classification: Application to Epilepsy Type Prediction Using PET Scan Data», Proceedings of the ICMLA, Pages:965-970, 2016.
  73. 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.
  74. D. Bendahan, G. Kozak-Ribbens, B. Ghattas, S. Confort-Gouny, and PJ. Cozzone. Métabolisme energétique musculaire de l'hyperthermie d'e?ort : Similitudes et différences avec l'hyperthermie maligne. In 1rst Congress in Myology, Nice, 2000.
  75. D. Bendahan, G. Kozak-Ribbens, S. Confort-Gouny, B. Ghattas, and PJ. Cozzone. 31p mrs evidences abnormal muscle energetics in patients who have suffered from exertional heat stroke : A comparison with malignant hyperthermia. In Proceedings of the Seventh meeting of the International Society for Magnetic Resonance in Medecine., Philadelphia, 1999.
  76. B. Ghattas. Statistical prediction of daily maximal ozone concentration, for the bouches du rhône department in france : Methods and strategies. In Proceedings of the 8th international symposium COST-319 Final Conference on Transport and Air Pollution, Graz- Austria, 1999.
  77. Book chapter / Chapitre de livre

  78. 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.

Working papers, Preprints