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Interpretation of the results of anatomical and embryological studies relies heavily on proper visualization of complex morphogenetic processes and patterns of gene expression in a three-dimensional (3D) context. However, reconstruction of complete 3D datasets is time consuming and often researchers study only a few sections. To help in understanding the resulting 2D data we developed a program (TRACTS) that places such arbitrary histological sections into a high-resolution 3D model of the developing heart. The program places sections correctly, robustly and as precisely as the best of the fits achieved by five morphology experts. Dissemination of 3D data is severely hampered by the 2D medium of print publication. Many insights gained from studying the 3D object are very hard to convey using 2D images and are consequently lost or cannot be verified independently. It is possible to embed 3D objects into a pdf document, which is a format widely used for the distribution of scientific papers. Using the freeware program Adobe Reader to interact with these 3D objects is reasonably straightforward; creating such objects is not. We have developed a protocol that describes, step by step, how 3D objects can be embedded into a pdf document. Both the use of TRACTS and the inclusion of 3D objects in pdf documents can help in the interpretation of 2D and 3D data, and will thus optimize communication on morphological issues in developmental biology.

Tertiary teledermatology (TTD), where a general dermatologist consults a specialized dermatologist on difficult cases, is a relatively new telemedicine service. We evaluated TTD in a Dutch university hospital, where 13 general dermatologists used TTD to consult 11 specialized dermatologists and two residents at the university medical centre. We measured the avoided referrals to the university centre, the usability of the system and the user acceptance of it. During a three-month study, general dermatologists consulted via TTD 28 times. In 17 of the consultations (61%), the general dermatologists would have referred their patients to the university centre if teledermatology had not been available. Referral was not necessary after teledermatology for 12 of these 17 consultations (71%). The mean usability score (0–100) of all the users was 80. All dermatologists were satisfied with TTD (mean satisfaction of 7.6 on a 10-point scale) and acceptance was high. The baseline measurements showed that half of tertiary referrals were suitable for TTD. These results suggest that TTD reduces unnecessary physical referrals and that users are satisfied with it. A large-scale evaluation is now required.

To unravel regulatory networks of genes functioning during embryonic development, information on in situ gene expression is required. Enormous amounts of such data are available in literature, where each paper reports on a limited number of genes and developmental stages. The best way to make these data accessible is via spatio-temporal gene expression atlases. Eleven atlases, describing developing vertebrates and covering at least 100 genes, were reviewed. This review focuses on: (i) the used anatomical framework, (ii) the handling of input data and (iii) the retrieval of information. Our aim is to provide insights into both the possibilities of the atlases, as well as to describe what more than a decade of developmental gene expression atlases can teach us about the requirements of the design of the 'ideal atlas'. This review shows that most ingredients needed to develop the ideal atlas are already applied to some extent in at least one of the discussed atlases. A review of these atlases shows that the ideal atlas should be based on a spatial framework, i.e. a series of 3D reference models, which is anatomically annotated using an ontology with sufficient resolution, both for relations as well as for anatomical terms.

Summary Objectives: To develop a predictive model for the outcome length of stay at the Intensive Care Unit (ICU LOS), including the choice of an optimal dichotomization threshold for this outcome. Reduction of prediction problems of this type of outcome to a two-class problem is a common strategy to identify high-risk patients. Methods: Threshold selection and model development are performed simultaneously. From the range of possible threshold values, the value is chosen for which the corresponding predictive model has maximal precision based on the data. To compare the precision of models for different dichotomizations of the outcome, the MALOR performance statistic is introduced. This statistic is insensitive to the prevalence of positive cases in a two-class prediction problem. Results: The procedure is applied to data from cardiac surgery patients to dichotomize the outcome ICU LOS. The class probabilitytree method is used to develop predictive models. Within our data, the best model precision is found at the threshold of seven days. Conclusions: The presented method extends existing procedures for predictive modeling with optimization of the outcome definition for predictive purposes. The method can be applied to all prediction problems where the outcome variable needs to be dichotomized, and is insensitive to changes in the prevalence of positive cases with different dichotomization thresholds.

In this paper, we describe an approach to handling partially specified probabilistic information. We propose a formalism, called Partial Probability Theory (PPT), which allows very general representations of belief states, and we give brief treatments of problems, like belief change, evidence combination, and decision making in the context of PPT. We argue that the generality of PPT provide new insights in all the mentioned problem areas. More detailed treatments of these issues can be found in several papers referred to in the text.

Telemedicine is becoming widely used in healthcare. Dermatology, because of its visual character, is especially suitable for telemedicine applications. Most common is teledermatology between general practitioners and dermatologists (secondary teledermatology). Another form of the teledermatology process is communication among dermatologists (tertiary teledermatology). The objective of this systematic review is to give an overview of studies on tertiary teledermatology with emphasis on the categories of use. A systematic literature search on tertiary teledermatology studies used all databases of the Cochrane Library, MEDLINE (1966-November 2007) and EMBASE (1980-November 2007). Categories of use were identified for all included articles and the modalities of tertiary teledermatology were extracted, together with technology, the setting the outcome measures, and their results. The search resulted in 1,377 publications, of which 11 were included. Four categories of use were found: getting an expert opinion from a specialized, often academic dermatologist (6/11); resident training (2/11); continuing medical education (4/11); and second opinion from a nonspecialized dermatologist (2/11). Three modalities were found: a teledermatology consultation application (7/11), a Web site (2/11), and an e-mail list (1/11). The majority (7/11) used store-and-forward, and 3/11 used store-and-forward and real-time. Outcome measures mentioned were learning effect (6), costs (5), diagnostic accuracy (1), validity (2) and reliability (2), patient and physician satisfaction (1), and efficiency improvement (3). Tertiary teledermatology's main category of use is getting an expert opinion from a specialized, often academic dermatologist. Tertiary teledermatology research is still in early development. Future research should focus on identifying the scale of tertiary teledermatology and on what modality of teledermatology is most suited for what purpose in communication among dermatologists.

Volume data, such as 3D reconstructions from histological sections orMRI and CT data, are commonly used in studies in biology and medicine. The quantification of morphological parameters and changes within a region of interest is a key concern in such studies. Specifically, it is often required to measure the distance between two points. These distance measurements have to follow a track through the tissue when measuring in sheetlike or contorted organs like the developing heart. A tool was developed that enables this kind of distance measurements. Three existing neighborhood estimators were compared; two of Verwer and one of Kiryati, all originally designed to compute chamfer distances in data sets with isotropic, cubic voxels. The estimators were therefore adjusted to handle non-isotropic data sets. Moreover, the shortest path along a track within a given tissue was calculated. The measurement of known distances, through a simplified model of an early heart tube, with anisotropic voxels was used decide which of the three estimators should be implemented. The observed Root Mean Square (RMS) errors were similar to the ones reported in literature in the unrestrained isotropic case. The adjusted Verwer estimator measuring in a 53 neighborhood performed best by far with the lowest mean and RMS errors.

For real-time monitoring of PCR amplification of DNA, quantitative PCR (qPCR) assays use various fluorescent reporters. DNA binding molecules and hybridization reporters (primers and probes) only fluoresce when bound to DNA and result in the non-cumulative increase in observed fluorescence. Hydrolysis reporters (TaqMan probes and QZyme primers) become fluorescent during DNA elongation and the released fluorophore remains fluorescent during further cycles; this results in a cumulative increase in observed fluorescence. Although the quantification threshold is reached at a lower number of cycles when fluorescence accumulates, in qPCR analysis no distinction is made between the two types of data sets. Mathematical modeling shows that ignoring the cumulative nature of the data leaves the estimated PCR efficiency practically unaffected but will lead to at least one cycle underestimation of the quantification cycle (C(q) value), corresponding to a 2-fold overestimation of target quantity. The effect on the target-reference ratio depends on the PCR efficiency of the target and reference amplicons. The leftward shift of the C(q) value is dependent on the PCR efficiency and with sufficiently large C(q) values, this shift is constant. This allows the C(q) to be corrected and unbiased target quantities to be obtained.

This paper presents a method to choose the threshold for dichotomization of survival outcomes in a structured fashion based on data analysis. The method is illustrated with an application to the prediction problem of the outcome length of stay at Intensive Care Unit (ICU LOS). Threshold selection is based on comparing the calibration of predictive models for dichotomized outcomes with increasing threshold values. To quantify model calibration a measure insensitive to class unbalance is used. The threshold value for which the associated predictive model has superior calibration is selected, and the corresponding model is used in practice. Using this method to select the threshold for ICU LOS, the best model calibration is found at a threshold of five days.

A variant of Reiter's default logic is proposed as a logic for reasoning with (defeasible) observations. Traditionally, default rules are assumed to represent generic information and the facts are assumed to represent specific information about the situation, but in this paper, the specific information derives from defeasible observations represented by (normal free) default rules, and the facts represent (hard) background knowledge. Whenever the evidence underlying some observation is more refined than the evidence underlying another observation, this is modelled by means of a priority between the default rules representing the observations. We thus arrive at an interpretation of prioritized normal free default logic as an observation logic, and we propose a semantics for this observation logic. Finally, we discuss how the proposed observation logic relates to the multiple extension problem and the problem of sensor fusion. (C) 2004 Elsevier B.V. All rights reserved

In this paper, we discuss the problem of combining several pieces of uncertain evidence, such as provided by symptoms, expert opinions, or sensor readings. Several of the proposed methods for combining evidence are reviewed and criticized. We argue for the position that (1) in general these proposed methods are inadequate, (2) strictly speaking, the only justifiable solution is to carefully model the situation, (3) a careful modelling of the situation requires a distinction between ignorance and uncertainty, and (4) drawing useful conclusions in the presence of ignorance may require additional assumptions which are not derivable from the available evidence.

This paper provides an introduction to the field of reasoning with uncertainty in Artificial Intelligence (AI), with an emphasis on reasoning with numeric uncertainty. The considered formalisms are Probability Theory and some of its generalizations, the Certainty Factor Model, Dempster-Shafer Theory, and Probabilistic Networks.

Shoham, proposed, a uniform approach to systems for nonmonotonic reasoning, which consists in considering standard logics augmented with a preference relation on the interpretations. Circumscription can easily -seen. to be a special case of this preference logic framework, butcapturing default logic turned out to-be, more difficult, and is even thought to be impossible bysome researchers of nonmonotonic reasoning. In this paper a preferential model semantics fordefault logic is given, by defining a preference relation on partial models called hypervaluations.Alternatively, Kripke models for K45 could have been used instead of hypervaluations. Thegiven semantics slightly strengthens Shoham's notion of preferential entailment, and reflectionon the question why such a strengthening is necessary provides some insight into the relationbetween default logic and circumscription.1980 Mathematical Subject Classification: B22, B501987 Computing Reviews- Classification: 1.2.3 Key words- and phrases: nonmonotonic resoning, default logic, preference ordering, partial

In this paper, we study the logical relations between different notions of knowledge and belief by means of generalizations of the usual Kripke models for epistemic logic. We argue that the obtained generalized Kripke models might be useful for carefully distinguishing the many different notions of knowledge and belief. We identify the (highly idealized) notions of objective knowledge and rational (introspective) belief, which correspond with fairly standard notions of knowledge and belief, and propose a system OKRIB for combining both notions which differs essentially from some other such proposals found in the literature. We also consider some other notions of knowledge and belief, and study how they relate to objective knowledge and rational belief.

An often mentioned obstacle for the use of Dempster-Shafer theory for the handling of uncertainty in expert systems is the computational complexity of the theory. One cause of this complexity is the fact that in Dempster-Shafer theory the evidence is represented by a belief function which is induced by a basic probability assignment, i.e. a probability measure on the powerset of possible answers to a question, and not by a probability measure on the set of possible answers to a question, like in a Bayesian approach. In this paper, we define a Bayesian approximation of a belief function and show that combining the Bayesian approximations of belief functions is computationally less involving than combining the belief functions themselves, while in many practical applications replacing the belief functions by their Bayesian approximations will not essentially affect the result.

Alternative proofs for Guaspari and Solovay's completeness theorems for R are presented. R is an extension of the provability logic L and was developed in order to study the formal properties of the provability predicate of PA occurring in sentences that may contain connectives for witness comparison. The proof of the Kripke model completeness theorems employs tail models, as introduced by Visser, instead of the more usual finite Kripke models, which makes it possible to derive arithmetical completeness from Kripke model completeness by literally embedding Kripke models into PA. Our arithmetical completenes theorem form a solution to the problem of obtaining a completeness result with respect to a variety of orderings

In Dempster-Shafer theory it is claimed that the pooling of evidence is reflected by Dempster's rule of combination, provided certain requirements are met. The justification of this claim is problematic, since the existing formulations of the requirements for the use of Dempster's rule are not completely clear. In this paper, randomly coded messages, Shafer's canonical examples for Dempster-Shafer theory, are employed to clarify these requirements and to evaluate Dempster's rule. The range of applicability of Dempster-Shafer theory will turn out to be rather limited. Further, it will be argued that the mentioned requirements do not guarantee the validity of the rule and some possible additional conditions will be described.

In this paper we develop a system of deontic logic (LAO, the logic of actual obligation) with a rather limited scope: we are, only interested in obligations as far as they: are relevant for deciding what actions actually ought to be done in a particular situation, given some normative system N. In fact we are interested how actual obligations are derived from the prima facie ones implied by N. Hence statements expressing that certain states of affairs are obligatory, such as "the speed-limit ought to be 140 in stead of 100", fall out of the scope. (Roughly speaking LAO is what Castaneda calls a logic of "ought-to-do". (cf. [C]).) Since in LAO actions can be obligatory while assertions cannot, actions and assertions have to be strictly separated in the language of LAO.