HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis

Alpaydin E (2004) Introduction to machine learning. Adaptive computation and machine learning. MIT Press, Cambridge Armstrong TS, Cohen MZ, Weinberg J, Gilbert MR (2004) Imaging techniques in neuro-oncology. Semin Oncol Nurs 20(4):231–239 Arús C, Celda B, Dasmahapatra S, Dupplaw D, González-Vélez H, van Huffel S, Lewis P, Lluch i Ariet M, Mier M, Peet A, Robles M (2006) On the design of a web-based decision support system for brain tumour diagnosis using distributed agents. In: WI-IAT 2006. IEEE, Hong Kong, pp 208–211 Barton S, Howe F, Tomlins A, Cudlip S, Nicholson J, Bell B, Griffiths J (1999) Comparison of in vivo 1H MRS of human brain tumors with 1H HR-MAS spectroscopy of intact biopsy samples in vitro. Magn Reson Mater Phys 8(2):121–128 Beckett D (2007) Turtle—terse RDF triple language. ILRT University of Bristol. http://www.ilrt.bris.ac.uk/discovery/2004/01/turtle/ (Last accessed: 13 Feb 2007) Bellifemine F, Poggi A, Rimassa G (2001) JADE: a FIPA2000 compliant agent development environment. In: AGENTS’01. ACM Press, Montreal, pp 216–217 Bishop CM (2006) Pattern recognition and machine learning. Information Science and Statistics. Springer, New York Bizer C, Cyganiak R, Garbers J, Maresch O (2006) D2RQ-treating Non-RDF relational databases as virtual RDF graphs, v0.5 edn. Freie Universitat, Berlin Bray F, Sankila R, Ferlay J, Parkin DM (2002) Estimates of cancer incidence and mortality in Europe in 1995. Eur J Cancer 38(1):99–166 Brugali D, Sycara. K (2000) Towards agent oriented application frameworks. ACM Comput Surv 32(1):21–27 Dasmahapatra S, Dupplaw D, Hu B, Lewis PH, Shadbolt N (2005) Ontology-mediated distributed decision support for breast cancer. In: AIME 2005. Lecture notes in computer science, vol 3581. Springer, Aberdeen, pp 221–225 De Turck F, Decruyenaere J, Thysebaert P, Van Hoecke S, Volckaert B, Danneels C, Colpaert K, De Moor G (2007) Design of a flexible platform for execution of medical decision support agents in the intensive care unit. Comput Biol Med 37(1):97–112 DeAngelis LM (2001) Brain tumors. N Engl J Med 344(2):114–123 Favre J, Taha JM, Burchiel KJ (2002) An analysis of the respective risks of hematoma formation in 361 consecutive morphological and functional stereotactic procedures. Neurosurgery 50(1):48–57 Field M, Witham TF, Flickinger JC, Kondziolka D, Lunsford LD (2001) Comprehensive assessment of hemorrhage risks and outcomes after stereotactic brain biopsy. J Neurosurg 94(4):545–551 Fletcher-Heath LM, Hall LO, Goldgof DB, Murtagh FR (2001) Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artif Intell Med 21(1–3):43–63 Gennari JH, Musen MA, Fergerson RW, Grosso WE (2003) Crubézy, M., Eriksson, H., N.F. Noy, S.W. Tu: The evolution of Protégé: an environment for knowledge-based systems development. Int J Hum-Comput Stud 58(1):89–123 Glotsos D, Tohka J, Ravazoula P, Cavouras D, Nikiforidis G (2005) Automated diagnosis of brain tumors astrocytomas using probabilistic neural network clustering and support vector machines. Int J Neural Syst 15(1–2):1–11 González-Vélez V, Flores-Rodríguez T, Flores-Avalos B, González-Vélez H (1997) A statistical brain-mapping system for the evaluation of communication disorders. In: CBMS 1997. IEEE, Maribor, pp 167–172 Hagberg G (1998) From magnetic resonance spectroscopy to classification of tumors. A review of pattern recognition methods. NMR Biomed 11(4–5):148–156 Hall W (1998) The safety and efficacy of stereotactic biopsy for intracranial lesions. Cancer 82(9):1749–1755 Hamdi MS (2006) MASACAD: A multiagent-based approach to information customization. IEEE Intell Syst 21(1):60–67 Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100(1):57–70 Haque S, Mital D, Srinivasan S (2002) Advances in biomedical informatics for the management of cancer. Ann NY Acad Sci 980:287–297 Hendler J (2001) Agents and the semantic web. IEEE Intell Syst 16(2):30–37 Howe FA, Opstad KS (2003) 1H MR spectroscopy of brain tumors and masses. NMR Biomed 16(3):123–131 IEEE Computer Society (2007) The foundation of intelligent physical agents. http://www.fipa.org/ (Last accessed 30 May 2007) Julià-Sapé M, Acosta D, Majós C, Moreno-Torres A, Wesseling P, Acebes JJ, Griffiths JR, Arús C (2006) Comparison between neuroimaging classifications and histopathological diagnoses using an international multicenter brain tumor magnetic resonance imaging database. J Neurosurg 105(1):6–14 Julià-Sapé M, Acosta D, Mier M, Arús C, Watson D (2006) The INTERPRET consortium: a multi-center web-accessible and quality control-checked database of in vivo MR spectra of brain tumour patients. Magn Reson Mater Phys 19(1):22–33 Larrañaga P, Calvo B, Santana R, Bielza C, Galdiano J, Inza I, Lozano JA, Armañanzas R, Santafé G, Perez A, Robles V (2006) Machine learning in bioinformatics. Brief Bioinform 7(1):86–112 Lee CS, Jiang CC, Hsieh TC (2006) A genetic fuzzy agent using ontology model for meeting scheduling system. Inf Sci 176(9):1131–1155 Lee CS, Pan CY (2004) An intelligent fuzzy agent for meeting scheduling decision support system. Fuzzy Sets Syst 142(3):467–488 Lee CS, Wang MH (2007) Ontology-based intelligent healthcare agent and its application to respiratory waveform recognition. Expert Syst Appl 33(3):606–619 Luck M, Merelli E (2005) Agents in bioinformatics. Knowl Eng Rev 20(2):117–125 Lukas L, Devos A, Suykens JAK, Vanhamme L, Howe FA, Majós C, Moreno-Torres A, Graaf MVD, Tate AR, Arús C, Van Huffel S (2004) Brain tumor classification based on long echo proton MRS signals. Artif Intell Med 31(1):73–89 Martínez-Bisbal MC, Martí-Bonmatí L, Piquer J, Revert A, Ferrer P, Llácer JL, Piotto M, Assemat O, Celda B (2004) 1H and 13C HR-MAS spectroscopy of intact biopsy samples ex vivo and in vivo. NMR Biomed 17(4):191–205 McGuinness DL, van Harmelen F (2004) OWL web ontology language overview. Standard W3C Recommendation 10 February 2004, World Wide Web Consortium (W3C). http://www.w3.org/TR/owl-features/ (Last accessed 13 January 2007) Merelli E, Armano G, Cannata N, Corradini F, d’Inverno M, Doms A, Lord P, Martin A, Milanesi L, Möller S, Schroeder M, Luck M (2007) Agents in bioinformatics, computational and systems biology. Brief Bioinform 8(1):45–59 Mischel P, Cloughesy T, Nelson S (2004) DNA-microarray analysis of brain cancer: molecular classification for therapy. Nature Rev Neuroscie 5:782–792 Mitchell TM (1999) Machine learning and data mining. Commun ACM 42(11):30–36 Nutt CL, Mani DR, Betensky RA, Tamayo P, Cairncross JG, Ladd C, Pohl U, Hartmann C, McLaughlin ME, Batchelor TT, Black PM, von Deimling A, Pomeroy SL, Golub TR, Louis DN (2003) Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63:1602–1607 Peet AC, Leach MO, Pinkerton CR, Price P, Williams SR, Grundy RG (2005) The development of functional imaging in the diagnosis, management and understanding of childhood brain tumors. Pediatr Blood Cancer 44(2):103–113 Robertson D (2004) A lightweight coordination calculus for agent systems. In: DALT 2004. Lecture notes in computer science, vol 3476. Springer, New York, pp 183–197 Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293–300 Tate AR, Underwood J, Acosta DM, Julià-Sapé M, Majós C, Moreno-Torres A, Howe FA, van der Graaf M, Lefournier V, Murphy MM, Loosemore A, Ladroue C, Wesseling P, Bosson JL, Cabañas ME, Simonetti AW, Gajewicz W, Calvar J, Capdevila A, Wilkins PR, Bell BA, Rémy C, Heerschap A, Watson D, Griffiths JR, Arús C (2006) Development of a decision support system for diagnosis and grading of brain tumors using in vivo magnetic resonance single voxel spectra. NMR Biomed 19(4):411–434 The eTUMOUR Consortium (2004–2008) eTUMOUR. http://www.etumour.net (Last accessed: 5 January 2007) The HealthAgents Consortium (2006–2008) HealthAgents. http://www.healthagents.net (Last accessed: 5 January 2007) Tortajada S, García-Gómez JM, Vidal C, Arús C, Julià-Sapé M, Moreno A, Robles M (2006) Improved classification by pattern recognition of brain tumors combining long and short echo time 1H-MR spectra. In: ESMRMB 2006: 23rd annual scientific meeting. Magn Reson Mater Phys 19(1):168–169 Universitat Autònoma de Barcelona (2000–2002) INTERPRET project. http://azizu.uab.es/INTERPRET/ (Last accessed: 5 January 2007) Vapnik VN (1999) The nature of statistical learning theory 2nd edn. Statistics for engineering and information science. Springer, New York Yan H, Jiang Y, Zheng J, Peng C, Li Q (2006) A multilayer perceptron-based medical decision support system for heart disease diagnosis. Expert Syst Appl 30(2):272–281