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## Publications

Publications (53)

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 understandi...

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) bec...

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 expres...

Motivation:
Recent technological developments have enabled the possibility of genetic and genomic integrated data analysis approaches, where multiple omics data sets from various biological levels are combined and used to describe (disease) phenotypic variations. The main goal is to explain and ultimately predict phenotypic variations by understan...

The AGM theory of belief revision has become an important paradigm for
investigating rational belief changes. Unfortunately, researchers working in
this paradigm have restricted much of their attention to rather simple
representations of belief states, namely logically closed sets of propositional
sentences. In our opinion, this has resulted in a t...

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 mea...

Volume data, such as 3D reconstructions from histological sections or MRI 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 dis...

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 (tertia...

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.
Threshold selection and model developme...

Learning Bayesian networks from data has been proposed as a promising approach to infer regulatory gene networks using gene expression data. In this paper we apply this approach to two different inference problems: (1) learning a genetic network 'from scratch', i.e., without using any prior knowledge of the structure to be learned and (2) the 'miss...

In research in cardiac development it is unavoidable to use sections of biological tissue, and it is difficult to interpret these sections because of the complexity of the developing heart. 3D computer reconstructions can provide an anatomical context of such sections and make their interpretation easier. However, for practical reasons, researchers...

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, th...

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 pre- diction problem of the outcome length of stay at Intensive Care Unit (ICU LOS). Threshold selection is based on comparing the calibration of predictiv...

Objective: To select the optimal threshold for dichotomization of survival variables based on data. Reduction of the prediction problem of survival outcomes to a two-class prediction problem is often performed in medicine. In this process of dichotomization, a threshold value should be selected that defines the two-class prediction problem. This ar...

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 represent...

Plan recognition can roughly be described as the problem of finding the plan(s) underlying the observed behaviour of agent(s). Of course, usually, the observed behaviour and available background knowledge does not determine the underlying plan, and therefore one can typically at best generate (reasonable) plan hypotheses. Traditionally, plan recogn...

This article deals with the problem of planning for robotic re surveillance in an oce building. It is shown that the planning search space, although it cannot be handled with traditional MDP solving methods, can be reduced through abstracting the environment and the expected cost. In this method the expected costs are computed per path and - given...

In this paper, we introduce a decision-theoretic strategy for surveillance as a first step towards automating the planning of the movement of an autonomous surveillance robot. In our opinion, this particular application is interesting in its own right, but it also provides a test-case for formalisms aimed at dealing both with (low-level) sensor, lo...

This article deals with the problem of planningfor robotic re surveillance in an oce building.It is shown that the planning search space,although it cannot be handled with traditionalMDP solving methods, can be reduced throughabstracting the environment and the expectedcost. In this method the expected costs arecomputed per path and - given an appr...

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. W...

In this paper, a decision theoretic view of the goal of surveillance is adopted. Subsequently a very simple formal model of the environment is introduced with the purpose of defining and comparing surveillance strategies. Several existing surveillance strategies are discussed. Then our decision-theoretic strategy is proposed and compared with the e...

Surveillance as a first step towards automating the planning of
the movement of an autonomous surveillance robot. We extend a previous
proposal (N. Massios and F. Voorbraak, 1998), by including some
heuristics based on an abstract representation of the environment. We
show, using a concrete example, how these heuristics allow
computationally feasib...

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....

In this paper, we study decision making in situations where the outcomes of the options are (in general) uncertain, without making the assumption that this uncertainty can be exactly quantified by means of a (single) probability measure. In such situations of partial ignorance, the traditional notion of optimising by maximising expected utility is...

We study the problem of making decisions under partial ignorance,
or partially quantified uncertainty. This problem arises in many
applications in robotics and AI, and it has not yet got the attention it
deserves. The traditional decision rules of decision under risk and
under strict uncertainty (or complete ignorance) can naturally be
extended to...

The paper discusses probabilistic belief change, in particular the type of change occurring when information is added which is consistent with the old beliefs. In the AGM theory of belief revision this type of belief change is known as an expansion, and is usually considered to be easy compared to revision and contraction, the two other main types...

The paper discusses the problem of combining unreliable pieces of evidence in a (generalized) probabilistic setting. The popular Dempster's rule for combining evidence in Dempster-Shafer theory is criticized on two accounts. Firstly, Dempster's rule is claimed to be invalid, and secondly, the rule may fail to support intuitively acceptable conclusi...

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.

A variant is proposed of the preference-based semantics for nonmonotonic logics that was originally considered by Shoham (1987,1988). In this variant it is not assumed that preferences between standard models are aggregated into one preference order. This allows the capturing of all main nonmonotonic formalisms, including Default Logic of Reiter (1...

In this paper a generalization of Kripke models is proposed for systemizing the study of the many different epistemic notions that appear in the literature. The generalized Kripke models explicitly represent an agent's epistemic states to which the epistemic notions refer. Two central epistemic notions are identified: objective (S5) knowledge and r...

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, but capturing default logic turned out to be, more difficult, and is even though...

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 message...

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 idea...

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 primary example of sentences involving wit...

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 probabi...

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 d...

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 primary example of sentences involving wit...

A famous result obtained in the mid-seventies by David Lewis shows that a straightforward interpretation of probabilities of conditionals as conditional probabilities runs into serious trouble. In this paper we try to circumvent this trouble by defining extensions of probability functions, called conditional probability functions. We further defend...

In this note we study the relation between belief functions of Dempster-Shafer theory and inner measures induced by probability functions. In [3,4] Joe Halpern and Ron Fagin claim that these classes of functions are essentially the same, or, more precisely, that they are exactly the same in case the functions are defined on formulas rather than set...