Dionisio Acosta


I lecture the Clinical Knowledge and Decision Making module at the Centre for Health Informatics & Multidisciplinary Education (CHIME) at UCL. I am also principal software developer for the CREDO project. My role in the project is to develop software for decision support in Multidisciplinary Meeting, Genetic Risk Assessment, and Triple Assessment for breast cancer using Proforma technology.

I received a BSc in Computer Science Engineering (1992; Non-uniform parallel random variate generation using Gibbs Sampling) from Simon Bolivar University, Caracas, under the supervision of Dr. Luis R. Pericci. I was awarded a PhD in Biomedical Engineering (2002; Statistical Classification of Magnetic Resonance Imaging Data) from the University of Sussex, Brighton, under the supervision on Dr. Des Watson and Dr. Adrian Thomas.

My research interests are in clinical decision support systems, statistical pattern recognition, medical imaging, signal processing, biomedical computing and discrete mathematics.

Dr. Dionisio Acosta
Senior Research Associate
Centre for Health Informatics & Multidisciplinary Education (CHIME)
University College London
4th Floor Holborn Union Building
Highgate Hill
London N19 5LW UK

T: +44 (0) 20 7288 3367
E: d DOT acosta AT ucl DOT ac DOT uk

Publications

  • Acosta, D., Patkar, V., Fox, J., Keshtgar, M.: Challenges in delivering decision support systems: The MATE Experience. D. RiaƱo et al. (Eds.), KR4HC, Lecture Notes in Artificial Intelligence, vol. 5943, pp. 124-140, 2010.
  • Patkar, V., Acosta, D., Fox, J., Jones, A., Davidson, T., Keshtgar, M.: A novel evidence-adaptive computerised decision support system for breast cancer multidisciplinary meetings: results of an evaluation study. San Antonio Breast Cancer Conference, 2009.
  • Patkar, V., Acosta, D., Fox, J, Jones, A., Keshtgar, M.: A Computerised Decision Support System for Breast Multidisciplinary Meeting: a baseline prospective audit to validate the system.European Journal of Surgical Oncology (EJSO), Volume 34, Issue 10, pp. 1187, 2008.
  • M. Fernandez, D. Acosta, and A. Quiroz. Improving the precision of model parameters using model based signal enhancement and the linear minimal model following an IVGTT in the healthy man.Applied Mathematics and Computation, 2007. DOI:10.1016/j.amc.2007.05.044
  • M. van der Graff, M. Julià-Sapé, F. Howe, C. Majós, A. Moreno, M. Rijpkema, D. Acosta, K. Opstad, Y. van der Meulen, . Arús, and A. Heerschap. MRS quality assessment in a multicentre study on MRS-based classification of brain tumours. NMR in Biomedicine, 2007. DOI: 10.1002/nbm.1172
  • M. Julià-Sapé, D. Acosta, C. Majós, . Moreno, M. van der Graaf,. Arús, and D. Watson.
    A multicentric web-accesible and quality control-checked database of in-vivo mr spectra, with associated data of brain tumour patients.Journal of Magnetic Resonance Materials in Physics, Biology and Medicine, 19(1):22–33, February 2006.
  • M. Julià-Sapé, D. Acosta, C. Majós, A. Moreno, P. Wesseling, J. Acebes, J. Griffiths, and C. Arús. Comparison between radiological classifications and histopathological diagnoses in an multi-centre international brain tumor magnetic resonance database. Journal of Neurosurgery, 105(1):6–14, July 2006.
  • A. Tate, J. Underwood, D. Acosta, M. Julià-Sapé, C. Majós, A. Moreno, F. Howe, M. van der Graaf, V. Lefournier, A. Ziegler, M. Murphy, A. Loosemore, C. Ladroue, I. Ferrer, P. Wesseling, M. Peoc'h, A. Simonetti, W. Gajewicz, J. Calvar, P. Wilkins, A. Bell, C. Rémy, A. Heerschap, D. Watson, J. Griffiths, and C. Arús. Development of a decision support system for diagnosis and grading of brain tumours using in-vivo magnetic resonance single voxel spectra.NMR in Biomedicine, 19(4):411–434, June 2006.
  • M. Julià-Sapé, G. Mercadal, M. Serrallonga, J. Underwood, D. Acosta, and C. Arús. Brain tumor diagnosis with mrs: The single voxel decision-support system and its associated multicentric, internet-available database of 304 clinically validated patient cases. In Proceedings of the Radiological Society of North America RSNA 2005 (InfoRAD), Chicago, USA., December 2005.
  • M. Fernandez, D. Acosta, M. Villasana, and D. Streja. Enhancing parameter precision and the minimal modeling approach in type I diabetes. In Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, volume 1, pages 797–800. IEEE EMBS, IEEE Press, September 2004.
  • M. Julià-Sapé, D. Acosta, M. Mier, J. Montero, C. Arús, D. Watson, and INTERPRET Consortium. A multicentric and quality-control checked database of in-vivo mr spectra, with associated data of brain tumour patients. In ISMRM Syllabus, Workshop on Advances in Experimental and Clinical MR in Cancer Research, England, UK., October 2004. Third Place William G. Negendank Student Poster Competition.
  • D. Acosta, M. Julià-Sapé, M. Van Der Graff, M. Rijpkema, A. Moreno, C. Majós, F. Howe, C. Arús, and D. Watson. An automated empirical approach for quality control filtering of single voxel 1h spectra for brain tumour classification. In Magnetic Resonance Materials in Physics, Biology and Medicine-Proceedings ESMRMB, volume 15, page 140, Cannes, France, August 2002. ESMRMB, Elsevier.
  • M. Julià-Sapé, D. Acosta, C. Majós, P. Wesseling, Pujol. J., Gajewicz. W., B. A. Bell, Griffiths. J. R., and C. Arús. Comparison between radiological and histopathological diagnoses in a multicentre international brain tumour magnetic resonance database. In Magnetic Resonance Materials in Physics, Biology and Medicine-Proceedings ESMRMB, page 92, Cannes, France, August 2002. ESMRMB, Elsevier.
  • D. Acosta and D. J. Watson. EU IST-1999-10310 INTERPRET MR spectra data manipulation software. Project Deliverable D 2.1, Univesity of Sussex, School of Cognitive and Computing Sciences, Brighton, UK, April 2001.
  • D. Acosta and D. J. Watson. EU IST-1999-10310 INTERPRET MRS DBMS and associated documentation. Project Deliverable D 2.4, Univesity of Sussex, School of Cognitive and Computing Sciences, Brighton, UK, August 2001.
  • A. V. García Serrano, D. Acosta, and A. L. Thomas. Density distribution model extraction from 3d data. In Proceedings of the 17th Eurographics UK Conference, Cambridge, UK, April 1999.