Objective: Medical critiquing systems compare clinical actions performed by a physician with a pr... more Objective: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find dierences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case dierences exist, the critiquing system provides insight into the extent to which
Medical guidelines and protocols are documents aimed at improving the quality of medical care by ... more Medical guidelines and protocols are documents aimed at improving the quality of medical care by offering support in medical decision making in the form of management recommendations based on sci- entic evidence. Whereas medical guidelines are intended for nation-wide use, and thus omit medical management details that may differ among hospitals, medical protocols are aimed at local use within hos-
The use of a medical guideline can be seen as the exe- cution of computational tasks, sequentiall... more The use of a medical guideline can be seen as the exe- cution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a 'network of tasks', i.e., as a number of steps that have a specic function or goal. To investigate the quality
Principles of Knowledge Representation and Reasoning, 2004
The use of approximation as a method for dealing with com- plex problems is a fundamental researc... more The use of approximation as a method for dealing with com- plex problems is a fundamental research issue in Knowledge Representation. Using approximation in symbolic AI is not straightforward. Since many systems use some form of logic as representation, there is no obvious metric that tells us 'how far' an approximate solution is from the correct solution. This article shows
EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1(WP3.4) In this document we... more EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1(WP3.4) In this document we propose a general framework for reasoning with inconsistent ontologies. We present formal definitions of soundness, meaningfulness, local completeness, and maximal com- pleteness of an inconsistency reasoner. We propose and investigate a pre-processing algorithm and discuss the strategies of inconsistency reasoning based on pre-defined selection functions dealing with concept
EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1.1 (WP3.4) This document is... more EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1.1 (WP3.4) This document is an informal deliverable provided to SEKT WP3 partners. In this document, a general framework for reasoning with inconsistent ontologies is proposed. An inconsistency reasoner is one which is able to return meaningful answers to queries, given an inconsistent on- tology. The formal definitions of soundness, meaningfulness, local completeness,
IEEE Transactions on Knowledge and Data Engineering
The application of a medical guideline to the treatment of a patient's disease can be seen as... more The application of a medical guideline to the treatment of a patient's disease can be seen as the execution of tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks,¿ that is, as a sequence of steps that have a specific function or goal. In this paper, a novel methodology for verifying the quality of such guidelines is introduced. To investigate the quality of such guidelines, we propose to include medical background knowledge to task networks and to formalize criteria for good medical practice that a guideline should comply with. This framework was successfully applied to a guideline dealing with the management of diabetes mellitus type 2 by using KIV.
A rigorous development process of clinical practice guidelines through a systematic appraisal of ... more A rigorous development process of clinical practice guidelines through a systematic appraisal of available evidence is costly and time consuming. One way to reduce the costs and time, and avoid unnecessary duplication of effort of guideline development is by relying on a local adaptation approach of guidelines developed at the (inter)national level by expert groups. In this chapter we survey the work on guideline adaptation, which includes methodologies, case studies, assessment of effectiveness, and related work on guideline adaptation in the Artificial Intelligence community.
In health care, the trend of evidence-based medicine, has led medical specialists to develop medi... more In health care, the trend of evidence-based medicine, has led medical specialists to develop medical guidelines, which are large nontrivial documents suggesting the detailed steps t hat should be taken by health-care professionals in managing the disease in a patient. In the Protocure project the objective has been to a ssess the improvement of medical guidelines using formal methods. This pa- per reports on some of our findings and experiences in quality check- ing medical guidelines. In particular the formalisation of meta-level quality criteria for good practice medicine, which is used i n con- junction with medical background knowledge to verify the quality of a guideline dealing with the management of diabetes mellitus type 2 using the interactive theorem prover KIV. For comparison, analogous investigations have been performed with other techniques including automatic theorem proving and model checking.
Censoring is a typical problem of data gathering and recording. Specialized techniques are needed... more Censoring is a typical problem of data gathering and recording. Specialized techniques are needed to deal with censored (regression) data. Gaussian processes are Bayesian nonparametric models that provide state-of-the-art performance in regression tasks. In this paper we propose an extension of Gaussian process regression models to data in which some observations are subject to censoring. Since the model is not analytically tractable we use Expectation propagation to perform approximate inference on it.
Medical guidelines and protocols are documents aimed at improving the quality of medical care by ... more Medical guidelines and protocols are documents aimed at improving the quality of medical care by offering support in medical decision making in the form of management recommendations based on scientific evidence. Whereas medical guidelines are intended for nation-wide use, and thus omit medical management details that may differ among hospitals, medical protocols are aimed at local use, e.g., within hospitals, and, therefore, include more detailed information. Although a medical guideline and an associated protocol concerning the management of a particular disorder are related to each other, one question is to what extent they are different. Formal methods are applied to shed light on this issue. A Dutch medical guideline regarding the treatment of breast cancer, and a Dutch protocol based on it, are taken as an example.
In the last decades enormous advances have been made possible for modelling complex (physical) sy... more In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long running times of such models a promising approach has been to replace them by stochastic approximations based on a few model evaluations. In this paper we focus on the often occuring case that the system modelled has two types of inputs x = (xc, xe) with xc representing control variables and xe representing environmental variables. Typically, xc needs to be optimised, whereas xe are uncontrollable but are assumed to adhere to some distribution. In this paper we use a Bayesian approach to address this problem: we specify a prior distribution on the underlying function using a Gaussian process and use Bayesian Monte Carlo to obtain the objective function by integrating out environmental variables. Furthermore, we empirically evaluate several active learning criteria that were developed for the deterministic cas...
This paper presents a framework for optimizing the preference learning pro-cess. In many real-wor... more This paper presents a framework for optimizing the preference learning pro-cess. In many real-world applications in which preference learning is involved the avail-able training data is scarce and obtaining labeled training data is expensive. Luckily in many of the preference learning situations data is available from multiple subjects. We use the multi-task formalism to enhance the individual training data by making use of the preference information learned from other subjects. Furthermore, since obtain-ing labels is expensive, we optimally choose which data to ask a subject for labelling to obtain maximum of information about her/his preferences. This paradigm —called active learning— has hardly been studied in a multi-task formalism. We propose an alternative for the standard criteria in active learning which actively chooses queries by making use of the available preference data from other subjects. The advantage of this alternative is the reduced computation costs and reduced t...
We present an EM-algorithm for the problem of learning user preferences with Gaussian processes i... more We present an EM-algorithm for the problem of learning user preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data set and show that predictive results for sound quality perception of normal hearing and hearingimpaired subjects, in the context of pairwise comparison experiments, can be improved using the hierarchical model. * This research was funded by STW project 070605 and NWO VICI grant 639.023.604.
We present an EM-algorithm for the problem of learning preferences with semiparametric models der... more We present an EM-algorithm for the problem of learning preferences with semiparametric models derived from Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data set and show that predictive results for sound quality perception of hearing-impaired subjects, in the context of pairwise comparison experiments, can be improved using a hierarchical model.
In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable la... more In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, possibly noisy, labels from multiple annotators. Typically, annotators have different levels of expertise (i.e., novice, expert) and there is considerable diagreement among annotators. We present a Gaussian process (GP) approach to regression with multiple labels but no absolute gold standard. The GP framework provides a principled non-parametric framework that can automatically estimate the reliability of individual annotators from data without the need of prior knowledge. Experimental results show that the proposed GP multi-annotator model outperforms models that either average the training data or weigh individually learned single-annotator models.
In both developing and developed countries, the costs of delivering health care are increasingly ... more In both developing and developed countries, the costs of delivering health care are increasingly tak- ing a large proportion of the national gross domestic product (GDP). GDP, is one of several measures of the size of a regions’ economy. While developed countries have a good doctor to patient ratio, in developing countries the ratios are alarming (e.g., in Uganda
Objective: Medical critiquing systems compare clinical actions performed by a physician with a pr... more Objective: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find dierences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case dierences exist, the critiquing system provides insight into the extent to which
Medical guidelines and protocols are documents aimed at improving the quality of medical care by ... more Medical guidelines and protocols are documents aimed at improving the quality of medical care by offering support in medical decision making in the form of management recommendations based on sci- entic evidence. Whereas medical guidelines are intended for nation-wide use, and thus omit medical management details that may differ among hospitals, medical protocols are aimed at local use within hos-
The use of a medical guideline can be seen as the exe- cution of computational tasks, sequentiall... more The use of a medical guideline can be seen as the exe- cution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a 'network of tasks', i.e., as a number of steps that have a specic function or goal. To investigate the quality
Principles of Knowledge Representation and Reasoning, 2004
The use of approximation as a method for dealing with com- plex problems is a fundamental researc... more The use of approximation as a method for dealing with com- plex problems is a fundamental research issue in Knowledge Representation. Using approximation in symbolic AI is not straightforward. Since many systems use some form of logic as representation, there is no obvious metric that tells us 'how far' an approximate solution is from the correct solution. This article shows
EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1(WP3.4) In this document we... more EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1(WP3.4) In this document we propose a general framework for reasoning with inconsistent ontologies. We present formal definitions of soundness, meaningfulness, local completeness, and maximal com- pleteness of an inconsistency reasoner. We propose and investigate a pre-processing algorithm and discuss the strategies of inconsistency reasoning based on pre-defined selection functions dealing with concept
EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1.1 (WP3.4) This document is... more EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1.1 (WP3.4) This document is an informal deliverable provided to SEKT WP3 partners. In this document, a general framework for reasoning with inconsistent ontologies is proposed. An inconsistency reasoner is one which is able to return meaningful answers to queries, given an inconsistent on- tology. The formal definitions of soundness, meaningfulness, local completeness,
IEEE Transactions on Knowledge and Data Engineering
The application of a medical guideline to the treatment of a patient's disease can be seen as... more The application of a medical guideline to the treatment of a patient's disease can be seen as the execution of tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a "network of tasks,¿ that is, as a sequence of steps that have a specific function or goal. In this paper, a novel methodology for verifying the quality of such guidelines is introduced. To investigate the quality of such guidelines, we propose to include medical background knowledge to task networks and to formalize criteria for good medical practice that a guideline should comply with. This framework was successfully applied to a guideline dealing with the management of diabetes mellitus type 2 by using KIV.
A rigorous development process of clinical practice guidelines through a systematic appraisal of ... more A rigorous development process of clinical practice guidelines through a systematic appraisal of available evidence is costly and time consuming. One way to reduce the costs and time, and avoid unnecessary duplication of effort of guideline development is by relying on a local adaptation approach of guidelines developed at the (inter)national level by expert groups. In this chapter we survey the work on guideline adaptation, which includes methodologies, case studies, assessment of effectiveness, and related work on guideline adaptation in the Artificial Intelligence community.
In health care, the trend of evidence-based medicine, has led medical specialists to develop medi... more In health care, the trend of evidence-based medicine, has led medical specialists to develop medical guidelines, which are large nontrivial documents suggesting the detailed steps t hat should be taken by health-care professionals in managing the disease in a patient. In the Protocure project the objective has been to a ssess the improvement of medical guidelines using formal methods. This pa- per reports on some of our findings and experiences in quality check- ing medical guidelines. In particular the formalisation of meta-level quality criteria for good practice medicine, which is used i n con- junction with medical background knowledge to verify the quality of a guideline dealing with the management of diabetes mellitus type 2 using the interactive theorem prover KIV. For comparison, analogous investigations have been performed with other techniques including automatic theorem proving and model checking.
Censoring is a typical problem of data gathering and recording. Specialized techniques are needed... more Censoring is a typical problem of data gathering and recording. Specialized techniques are needed to deal with censored (regression) data. Gaussian processes are Bayesian nonparametric models that provide state-of-the-art performance in regression tasks. In this paper we propose an extension of Gaussian process regression models to data in which some observations are subject to censoring. Since the model is not analytically tractable we use Expectation propagation to perform approximate inference on it.
Medical guidelines and protocols are documents aimed at improving the quality of medical care by ... more Medical guidelines and protocols are documents aimed at improving the quality of medical care by offering support in medical decision making in the form of management recommendations based on scientific evidence. Whereas medical guidelines are intended for nation-wide use, and thus omit medical management details that may differ among hospitals, medical protocols are aimed at local use, e.g., within hospitals, and, therefore, include more detailed information. Although a medical guideline and an associated protocol concerning the management of a particular disorder are related to each other, one question is to what extent they are different. Formal methods are applied to shed light on this issue. A Dutch medical guideline regarding the treatment of breast cancer, and a Dutch protocol based on it, are taken as an example.
In the last decades enormous advances have been made possible for modelling complex (physical) sy... more In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long running times of such models a promising approach has been to replace them by stochastic approximations based on a few model evaluations. In this paper we focus on the often occuring case that the system modelled has two types of inputs x = (xc, xe) with xc representing control variables and xe representing environmental variables. Typically, xc needs to be optimised, whereas xe are uncontrollable but are assumed to adhere to some distribution. In this paper we use a Bayesian approach to address this problem: we specify a prior distribution on the underlying function using a Gaussian process and use Bayesian Monte Carlo to obtain the objective function by integrating out environmental variables. Furthermore, we empirically evaluate several active learning criteria that were developed for the deterministic cas...
This paper presents a framework for optimizing the preference learning pro-cess. In many real-wor... more This paper presents a framework for optimizing the preference learning pro-cess. In many real-world applications in which preference learning is involved the avail-able training data is scarce and obtaining labeled training data is expensive. Luckily in many of the preference learning situations data is available from multiple subjects. We use the multi-task formalism to enhance the individual training data by making use of the preference information learned from other subjects. Furthermore, since obtain-ing labels is expensive, we optimally choose which data to ask a subject for labelling to obtain maximum of information about her/his preferences. This paradigm —called active learning— has hardly been studied in a multi-task formalism. We propose an alternative for the standard criteria in active learning which actively chooses queries by making use of the available preference data from other subjects. The advantage of this alternative is the reduced computation costs and reduced t...
We present an EM-algorithm for the problem of learning user preferences with Gaussian processes i... more We present an EM-algorithm for the problem of learning user preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data set and show that predictive results for sound quality perception of normal hearing and hearingimpaired subjects, in the context of pairwise comparison experiments, can be improved using the hierarchical model. * This research was funded by STW project 070605 and NWO VICI grant 639.023.604.
We present an EM-algorithm for the problem of learning preferences with semiparametric models der... more We present an EM-algorithm for the problem of learning preferences with semiparametric models derived from Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data set and show that predictive results for sound quality perception of hearing-impaired subjects, in the context of pairwise comparison experiments, can be improved using a hierarchical model.
In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable la... more In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, possibly noisy, labels from multiple annotators. Typically, annotators have different levels of expertise (i.e., novice, expert) and there is considerable diagreement among annotators. We present a Gaussian process (GP) approach to regression with multiple labels but no absolute gold standard. The GP framework provides a principled non-parametric framework that can automatically estimate the reliability of individual annotators from data without the need of prior knowledge. Experimental results show that the proposed GP multi-annotator model outperforms models that either average the training data or weigh individually learned single-annotator models.
In both developing and developed countries, the costs of delivering health care are increasingly ... more In both developing and developed countries, the costs of delivering health care are increasingly tak- ing a large proportion of the national gross domestic product (GDP). GDP, is one of several measures of the size of a regions’ economy. While developed countries have a good doctor to patient ratio, in developing countries the ratios are alarming (e.g., in Uganda
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Papers by Perry Groot