| Ontology mapping : a way out of the medical Tower of Babel? | p. 3 |
| Human computer interaction in context aware wearable systems | p. 7 |
| A new approach to the abstraction of monitoring data in intensive care | p. 13 |
| Learning rules with complex temporal patterns in biomedical domains | p. 23 |
| Discriminating exanthematic diseases from temporal patterns of patient symptoms | p. 33 |
| Probabilistic abstraction of multiple longitudinal electronic medical records | p. 43 |
| Using a Bayesian-network model for the analysis of clinical time-series data | p. 48 |
| Data-driven analysis of blood glucose management effectiveness | p. 53 |
| Extending temporal databases to deal with telic/atelic medical data | p. 58 |
| Dichotomization of ICU length of stay based on model calibration | p. 67 |
| AtherEx : an expert system for atherosclerosis risk assessment | p. 79 |
| Smooth integration of decision support into an existing electronic patient record | p. 89 |
| REPS : a rehabilitation expert system for post-stroke patients | p. 94 |
| Testing Asbru guidelines and protocols for neonatal intensive care | p. 101 |
| EORCA : a collaborative activities representation for building guidelines from field observations | p. 111 |
| Design patterns for modelling medical guidelines | p. 121 |
| Improving clinical guideline implementation through prototypical design patterns | p. 126 |
| Automatic derivation of a decision tree to represent guideline-based therapeutic strategies for the management of chronic diseases | p. 131 |
| Exploiting decision theory for supporting therapy selection in computerized clinical guidelines | p. 136 |
| Helping physicians to organize guidelines within conceptual hierarchies | p. 141 |
| MHB - a many-headed bridge between informal and formal guideline representations | p. 146 |
| Clinical guidelines adaptation : managing authoring and versioning issues | p. 151 |
| Open-source publishing of medical knowledge for creation of computer-interpretable guidelines | p. 156 |
| A history-based algebra for quality-checking medical guidelines | p. 161 |
| The spock system : developing a runtime application engine for hybrid-Asbru guidelines | p. 166 |
| AI planning technology as a component of computerised clinical practice guidelines | p. 171 |
| Gaining process information from clinical practice guidelines using information extraction | p. 181 |
| Ontology-driven extraction of linguistic patterns for modelling clinical guidelines | p. 191 |
| Formalising medical quality indicators to improve guidelines | p. 201 |
| Oncology ontology in the NCI thesaurus | p. 213 |
| Ontology-mediated distributed decision support for breast cancer | p. 221 |
| Multimedia data management to assist tissue microarrays design | p. 226 |
| Building medical ontologies based on terminology extraction from texts : methodological propositions | p. 231 |
| Translating biomedical terms by inferring transducers | p. 236 |
| Using lexical and logical methods for the alignment of medical terminologies | p. 241 |
| Latent argumentative pruning for compact MEDLINE indexing | p. 246 |
| A benchmark evaluation of the French MeSH indexers | p. 251 |
| Populating an allergens ontology using natural language processing and machine learning techniques | p. 256 |
| Ontology of time and situoids in medical conceptual modeling | p. 266 |
| The use of verbal classification in determining the course of medical treatment by medicinal herbs | p. 276 |
| Interactive knowledge validation in CBR for decision support in medicine | p. 289 |
| Adaptation and medical case-based reasoning, focusing on endocrine therapy support | p. 300 |
| Transcranial magnetic stimulation (TMS) to evaluate and classify mental diseases using neural networks | p. 310 |
| Towards information visualization and clustering techniques for MRI data sets | p. 315 |
| Electrocardiographic imaging : towards automated interpretation of activation maps | p. 323 |
| Automatic landmarking of cephalograms by cellular neural networks | p. 333 |
| Anatomical sketch understanding : recognizing explicit and implicit structure | p. 343 |
| Morphometry of the hippocampus based on a deformable model and support vector machines | p. 353 |
| Automatic segmentation of whole-body bone scintigrams as a preprocessing step for computer assisted diagnostics | p. 363 |
| Multi-agent patient representation in primary care | p. 375 |
| Clinical reasoning learning with simulated patients | p. 385 |
| Implicit learning system for teaching the art of acute cardiac infarction diagnosis | p. 395 |
| Which kind of knowledge is suitable for redesigning hospital logistic processes? | p. 400 |
| Web mining techniques for automatic discovery of medical knowledge | p. 409 |
| Resource modeling and analysis of regional public health care data by means of knowledge technologies | p. 414 |
| An evolutionary divide and conquer method for long-term dietary menu planning | p. 419 |
| Human/computer interaction to learn scenarios from ICU multivariate time series | p. 424 |
| Mining clinical data : selecting decision support algorithm for the MET-AP system | p. 429 |
| A data pre-processing method to increase efficiency and accuracy in data mining | p. 434 |
| Rule discovery in epidemiologic surveillance data using EpiXCS : an evolutionary computation approach | p. 444 |
| Subgroup mining for interactive knowledge refinement | p. 453 |
| Evidence accumulation for identifying discriminatory signatures in biomedical spectra | p. 463 |
| On understanding and assessing feature selection bias | p. 468 |
| A model-based approach to visualizing classification decisions for patient diagnosis | p. 473 |
| Learning rules from multisource data for cardiac monitoring | p. 484 |
| Effective confidence region prediction using probability forecasters | p. 494 |
| Signature recognition methods for identifying influenza sequences | p. 504 |
| Conquering the curse of dimensionality in gene expression cancer diagnosis : tough problem, simple models | p. 514 |
| An algorithm to learn causal relations between genes from steady state data : simulation and its application to melanoma dataset | p. 524 |
| Relation mining over a corpus of scientific literature | p. 535 |
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