لایب سان

Abstract. Medical Informatics applies computer-based technologies to several aspects of medicine, including clinical practice, research and education. In all these fields different trends and interests can be identified, respectively related to methodology, technique, and health care policy, including cost-effectiveness analysis, armonization of efforts, budget management, quality assessment and support to medical decision- making. All the above aspects may take advantage of proper guidelines aimed at minimizing the misuse and unsuitability of health services, at identifying the appropriate strategies for health policy, and at suitably supporting clinical decisions.

Table of Contents Keynote Lectures From Clinical Guidelines to Decision Support . . . . . . . . . . . . . . . . . . . . . . . . . . 3 G. Molino Artificial Intelligence for Building Learning Health Care Organizations . . . . 13 M. Stefanelli Timing Is Everything: Temporal Reasoning and Temporal Data Maintenance in Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Y. Shahar Machine Learning for Data Mining in Medicine . . . . . . . . . . . . . . . . . . . . . . . . 47 N. Lavraˇc Guidelines and Protocols Guidelines-Based Workflow Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 S. Quaglini, C. Mossa, C. Fassino, M. Stefanelli, A. Cavallini, G. Micieli Enhancing Clinical Practice Guideline Compliance by Involving Physicians in the Decision Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 B. S ́eroussi, J. Bouaud, ́E.-C. Antoine Application of Therapeutic Protocols: A Tool to Manage Medical Knowledge 86 C. Sauvagnac, J. Stines, A. Lesur, P. Falzon, P. Bey Decision Support Systems, Knowledge-Based Systems, Cooperative Systems From Description to Decision: Towards a Decision Support Training System for MR Radiology of the Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 B. du Boulay, B. Teather, G. du Boulay, N. Jeffrey, D. Teather, M. Sharples, L. Cuthbert Internet-Based Decision-Support Server for Acute Abdominal Pain . . . . . . . 103 H.P. Eich, C. Ohmann Multi-modal Reasoning in Diabetic Patient Management . . . . . . . . . . . . . . . . 113 S. Montani, R. Bellazzi, L. Portinale, A. Riva, M. Stefanelli X Table of Contents Experiences with Case-Based Reasoning Methods and Prototypes for Medical Knowledge-Based Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 R. Schmidt, B. Pollwein, L. Gierl Exploiting Social Reasoning of Open Multi-agent Systems to Enhance Cooperation in Hospitals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 S. Aknine Influence Diagrams for Neonatal Jaundice Management . . . . . . . . . . . . . . . . . 138 C. Bielza, S. R ́ıos-Insua, M. G ́omez Electronic Drug Prescribing and Administration - Bedside Medical Decision Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 I.R. Clark, B.A. McCauley, I.M. Young, P.G. Nightingale, M. Peters, N.T. Richards, D. Adu Neonatal Ventilation Tutor (VIE-NVT), a Teaching Program for the Mechanical Ventilation of Newborn Infants . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 W. Horn, C. Popow, C. Stocker, S. Miksch A Life-Cycle Based Authorisation Expert Database System . . . . . . . . . . . . . 153 Y.-L. O A Decision-Support System for the Identification, Staging, and Functional Evaluation of Liver Diseases (HEPASCORE) . . . . . . . . . . . . . . . . . . . . . . . . . . 158 M. Torchio, S. Battista, F. Bar, C. Pollet, M. Marzuoli, M.C. Bucchi, R. Pagni, G. Molino Model-Based Systems A Model-Based Approach for Learning to Identify Cardiac Arrhythmias . . 165 G. Carrault, M.-O. Cordier, R. Quiniou, M. Garreau, J.J. Bellanger, A. Bardou An Model-Based System for Pacemaker Reprogramming . . . . . . . . . . . . . . . . 175 P. Lucas, A. Tholen, G. van Oort Integrating Deep Biomedical Models into Medical Decision Support Systems: An Interval Constraint Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 J. Cruz, P. Barahona, F. Benhamou Neural Networks, Causal Probabilistic Networks A Decision Theoretic Approach to Empirical Treatment of Bacteraemia Originating from the Urinary Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 S. Andreassen, L. Leibovici, H.C. Schønheyder, B. Kristensen, C. Riekehr, A.G. Kjær, K.G. Olesen Table of Contents XI An ECG Ischemic Detection System Based on Self-Organizing Maps and a Sigmoid Function Pre-processing Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 E.A. Fernandez, J. Presedo, S. Barro Neural Network Recognition of Otoneurological Vertigo Diseases with Comparison of Some Other Classification Methods . . . . . . . . . . . . . . . . . . . . . 217 M. Juhola, J. Laurikkala, K. Viikki, Y. Auramo, E. Kentala, I. Pyykk ̈o A Comparison of Linear and Non-linear Classifiers for the Detection of Coronary Artery Disease in Stress-ECG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 G. Dorffner, E. Leitgeb, H. Koller The Case-Based Neural Network Model and Its Use in Medical Expert Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232 W. Goodridge, H. Peter, A. Abayomi Knowledge Representation A Medical Ontology Library That Integrates the UMLS MetathesaurusTM 239 D.M. Pisanelli, A. Gangemi, G. Steve The Use of the UMLS Knowledge Sources for the Design of a Domain Specific Ontology: A Practical Experience in Blood Transfusion . . . . . . . . . . 249 S. Achour, M. Dojat, J.-M. Brethon, G. Blain, E. Lepage Representing Knowledge Levels in Clinical Guidelines . . . . . . . . . . . . . . . . . . . 254 P. Terenziani, P. Raviola, O. Bruschi, M. Torchio, M. Marzuoli, G. Molino Temporal Reasoning Intelligent Analysis of Clinical Time Series by Combining Structural Filtering and Temporal Abstractions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 R. Bellazzi, C. Larizza, P. Magni, S. Montani, G. De Nicolao Knowledge-Based Event Detection in Complex Time Series Data . . . . . . . . . 271 J. Hunter, N. McIntosh Abstracting Steady Qualitative Descriptions over Time from Noisy, High-Frequency Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 S. Miksch, A. Seyfang, W. Horn, C. Popow Visualization Techniques for Time-Oriented, Skeletal Plans in Medical Therapy Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 R. Kosara, S. Miksch Visualizing Temporal Clinical Data on the WWW . . . . . . . . . . . . . . . . . . . . . . 301 C. Combi, L. Portoni, F. Pinciroli XII Table of Contents Machine Learning Machine Learning in Stepwise Diagnostic Process . . . . . . . . . . . . . . . . . . . . . . 315 M. Kukar, C. Groˇselj Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . 326 S. Mani, M.B. Dick, M.J. Pazzani, E.L. Teng, D. Kempler, I.M. Taussig The Analysis of Head Inquiry Data Using Decision Tree Techniques . . . . . . 336 A. McQuatt, P.J.D. Andrews, D. Sleeman, V. Corruble, P.A. Jones Machine Learning for Survival Analysis: A Case Study on Recurrence of Prostate Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 B. Zupan, J. Demˇsar, M.W. Kattan, J.R. Beck, I. Bratko ICU Patient State Characterization Using Machine Learning in a Time Series Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 D. Calvelo, M.-C. Chambrin, D. Pomorski, P. Ravaux Diagnostic Rules of Increased Reliability for Critical Medical Applications . 361 D. Gamberger, N. Lavraˇc, C. Groˇselj Machine Learning Inspired Approaches to Combine Standard Medical Measures at an Intensive Care Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 B. Sierra, N. Serrano, P. Larra ̃naga, E.J. Plasencia, I. Inza, J.J. Jim ́enez, J.M. De la Rosa, M.L. Mora A Screening Technique for Prostate Cancer by Hair Chemical Analysis and Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372 P. Wu, K.L. Heng, S.W. Yang, Y.F. Chen, R.S. Mohan, P.H.C. Lim Natural Language Processing A Conversational Model for Health Promotion on the World Wide Web . . . 379 A. Cawsey, F. Grasso, R. Jones Types of Knowledge Required to Personalize Smoking Cessation Letters . . 389 E. Reiter, R. Robertson, L. Osman Small Is Beautiful - Compact Semantics for Medical Language Processing . 400 M. Romacker, S. Schulz, U. Hahn Speech Driven Natural Language Understanding for Hands-Busy Recording of Clinical Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 D.J. Barker, S.C. Lynch, D.S. Simpson, W.A. Corbett Table of Contents XIII Automatic Acquisition of Morphological Knowledge for Medical Language Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 P. Zweigenbaum, N. Grabar Image Processing and Computer Aided Design A Multi-agent System for MRI Brain Segmentation . . . . . . . . . . . . . . . . . . . . 423 L. Germond, M. Dojat, C. Taylor, C. Garbay Modelling Blood Vessels of the Eye with Parametric L-Systems Using Evolutionary Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 G. K ́okai, Z. T ́oth, R. V ́anyi Animating Medical and Safety Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 P. Hammond, P. Wells, S. Modgil Active Shape Models for Customised Prosthesis Design . . . . . . . . . . . . . . . . . 448 T.J. Hutton, P. Hammond, J.C. Davenport Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453

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