Annette Ten Teije

Vrije Universiteit Amsterdam | VU · Department of Computer Science

Understanding the rationale behind the predictions made by machine learning models holds paramount importance across numerous applications. Various explainable models have been developed to shed light on these predictions by assessing the individual contributions of features to the outcome of black-box models. However, existing methods often overlo...

We propose a method that allows to develop shared understanding between two agents for the purpose of performing a task that requires cooperation. Our method focuses on efficiently establishing successful task-oriented communication in an open multi-agent system, where the agents do not know anything about each other and can only communicate via gr...

We study the problem of combining neural networks with symbolic reasoning. Recently introduced frameworks for Probabilistic Neurosymbolic Learning (PNL), such as DeepProbLog, perform exponential-time exact inference, limiting the scalability of PNL solutions. We introduce Approximate Neurosymbolic Inference (A-NeSI): a new framework for PNL that us...

The unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognized as one of the key challenges of modern AI. Recent years have seen a large number of publications on such hybrid neuro-symbolic AI systems. That rapidly growing literature is highly diverse, mostly empirical, and is lacking a unifying view of th...

Background: In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representation of medical knowledge for supporting clinical care. Contributions regarding modeling languages,...

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulat...

This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event. The 18 revised full papers included in this volume were carefully selected from th...

Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end, th...

This paper presents a method for formally representing Computer-Interpretable Guidelines. It allows for combining them with knowledge from several sources to better detect potential interactions within multimorbidity cases, coping with possibly conflicting pieces of evidence coming from clinical studies. The originality of our approach is on the ca...

Clinical Guidelines are important knowledge resources for medical decision making. They provide clinical recommendations based on a collection of research findings with respect to a specific disease. Since, new findings are regularly published, CGs are also expected to be regularly updated. However, selecting and analysing medical publications requ...

Clinical quality indicators are tools to measure the quality of healthcare and can be classified into structure-related, process-related and outcome-related indicators. The objective of this study is to investigate whether Electronic Medical Record (EMR) data from a Chinese diabetes specialty hospital can be used for the automated computation of a...

Evidence-based medical guidelines are systematically developed recommendations with the aim to assist practitioner and patients decisions regarding appropriate health care for specific clinical circumstances, and are based on evidence described in medical research papers. Evidence-based medical guidelines should be regularly updated, such that they...

SWISH provides a general purpose collaborative infrastructure for applying Prolog reasoning over an RDF dataset together with features that facilitates prototyping Semantic Web applications. In this paper we report on the use of SWISH for efficiently developing a prototype for detection of clinical guideline interactions. These guidelines are a set...

Rule-based formalization of eligibility criteria in clinical trials have distinguished features such as declaration, easy maintenance, reusability, and expressiveness. In this paper, we present several knowledge services which can be provided by the rule-based formalization of eligibility criteria. The rule-based formalization can be generated auto...

Computer-Interpretable Guidelines (CIGs) are representations of Clinical Guidelines (CGs) in computer interpretable languages. CIGs have been pointed as an alternative to deal with the various limitations of paper based CGs to support healthcare activities. Although the improvements o�ered by existing CIG languages, the complexity of the medical do...

Over the past years, research utilizing routine care data extracted from Electronic Medical Records (EMRs) has increased tremendously. Yet there are no straightforward, standardized strategies for pre-processing these data. We propose a dedicated medical pre-processing pipeline aimed at taking on many problems and opportunities contained within EMR...

The formal representation of clinical knowledge is still an open research topic. Classical representation languages for clinical guidelines are used to produce diagnostic and treatment plans. However, they have important limitations, e.g. when looking for ways to re-use, combine, and reason over existing clinical knowledge. These limitations are es...

Evidence-based Medical guidelines are developed based on the best available evidence in biomedical science and clinical practice. Such evidence-based medical guidelines should be regularly updated, so that they can optimally serve medical practice by using the latest evidence from medical research. The usual approach to detect such new evidence is...

Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. This paper intr...

Background: Early diagnosis of colorectal cancer (CRC) is likely to reduce burden of disease and improve treatment success. Estimation of the individual patient risk for CRC diagnostic determinants in a primary care setting has not been very successful as yet. The aim of our study is to improve prediction of CRC in patients selected for colonoscop...

Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recom- mendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end,...

Evidence-based medical guidelines contain a collection of recommendations which have been created using the best clinical research findings (a.k.a. evidences) of the highest value to aid in the delivery of optimum clinical care to patients. In evidence-based medical guidelines, the conclusions (a.k.a. recommendations) are marked with different evid...

To ensure timely use of new results from medical research in daily medical practice, evidence-based medical guidelines must be updated using the latest medical articles as evidences. Finding such new relevant medical evidence manually is time consuming and labor intensive. Traditional information retrieval methods can improve the efficiency of find...

Electronic Medical Records (EMRs) provide a wealth of data that can be used to generate predictive models for diseases. Quite some studies have been performed that use EMRs to generate such models for specific diseases, but most of them are based on more traditional techniques used in medical domain, such as logistic regression. This paper studies...

While almost all dictionary compression techniques focus on static RDF data, we present a compact in-memory RDF dictionary for dynamic and streaming data. To do so, we analysed the structure of terms in real-world datasets and observed a high degree of common prefixes. We studied the applicability of Trie data structures on RDF data to reduce the m...

Patient recruitment is one of the most important barriers to successful completion of clinical trials and thus to obtaining evidence about new methods for prevention, diagnostics and treatment. The reason is that recruitment is effort consuming. It requires the identification of candidate patients for the trial (the population under study), and ver...

Medical guidelines are documents that describe optimal treatment for patients by medical practitioners based on current medical research (evidence), in the form of step-by-step recommendations. Because the field of medical research is very large and always evolving, keeping these guidelines up-to-date with the current state of the art is a difficul...

This book constitutes the thoroughly refereed post-workshop proceedings of two workshops held at the International Conference on Artificial Intelligence in Medicine, AIME 2015, held in Pavia, Italy, in June 2015: the 7th International Workshop on Knowledge Representation for Health Care, KR4HC 2015, and the 8th International Workshop on Process-ori...

Representation of clinical knowledge is still an open research topic. In particular, classical languages designed for representing clini- cal guidelines, which were meant for producing diagnostic and treatment plans, present limitations such as for re-using, combining, and reasoning over existing knowledge. In this paper, we address such limitation...

Evidence-based Clinical Guidelines are the document or recommendation which follow a rigorous development process and are based on the highest quality scientific evidence. Evidence-based clinical guidelines are important knowledge resources which have been used in many medical decision support systems and medical applications. In this paper, we pre...

Computer-Interpretable Guidelines (CIGs) are representations of Clinical Guidelines (CGs) in computer interpretable languages. CIGs have been pointed as an alternative to deal with the various limitations of paper based CGs to support healthcare activities. Although the improvements o�ered by existing CIG languages, the complexity of the medical do...

Evidence-based Clinical Guidelines (EbCGs) are document or recommendation which have been created using the best clinical research findings of the highest value to aid in the delivery of optimum clinical care to patients. In this paper, we propose a lightweight formalism of evidence-based clinical guidelines by introducing the Semantic Web Technolo...

Our study aims to assess the influence of data quality on computed Dutch hospital quality indicators, and whether colorectal cancer surgery indicators can be computed reliably based on routinely recorded data from an electronic medical record (EMR). Cross-sectional study in a department of gastrointestinal oncology in a university hospital, in whic...

Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a m...

Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality ind...

The presented work contributes to bridging the representa-tion of clinical trials and patient data. Our ultimate goal is to support the trial recruitment, by automating the process of formalizing eligibility criteria of clinical trials, starting from free text of criteria and leading to a computable representation. This paper discusses the final st...

In this paper, we propose a rule-based formalization of eligibility criteria for clinical trials. The rule-based formalization is implemented by using the logic programming language Prolog. Compared with existing formalizations such as pattern-based and script-based languages, the rule-based formalization has the advantages of being declarative, ex...

Objective: This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated comput...

Since eligibility criteria of clinical trials are represented as free text, their automatic interpretation and the eval-uation of patient eligibility is challenging. Our approach to the criteria processing is based on the identification of contextual patterns and semantic concepts that together define the machine-interpretable meaning. The goal of...

In this paper, we propose an approach of semantically enabled systems for clinical trials. The goals are not only to achieve the interoperability by semantic integration of heterogeneous data in clinical trials, but also to facilitate automatic reasoning and data processing services for decision support systems in various settings of clinical trial...

The development and investigation of medical applications require patient data from various Electronic Health Records (EHR) or Clinical Records (CR). However, in practice, patient data is and should be protected and monitored to avoid unauthorized access or publicity, because of many reasons including privacy, security, ethics, and confidentiality....

This book constitutes the thoroughly refereed papers from the BPM 2013 Joint Workshop on Process-Oriented Information Systems and Knowledge Representation in Health Care, KR4HC 2013/ProHealth 2013, held in Murcia, Spain, in June 2013. The 10 revised full papers presented together with 1 keynote paper were carefully reviewed and selected from 19 sub...

This book constitutes thoroughly refereed revised selected papers from the BPM 2012 Joint Workshop on Process-Oriented Information Systems and Knowledge Representation in Health Care, ProHealth 2012/KR4HC 2012, held in Tallinn, Estonia, in September 2012. The 9 papers presented were carefully reviewed and selected from 19 submissions. In addition t...

The semi-automatic evaluation of eligibility crite-ria can facilitate the recruitment for clinical trials, timely com-pletion of studies and generation of clinical evidence about new approaches to treatment, prevention and diagnosis. Because eligibility criteria are represented as free text, automatically extracting their meaning and evaluating the...

Electronic Health Records (EHRs) contain a wealth of information, but accessing and (re)using it is often difficult. Archetypes have been shown to facilitate the (re)use of EHR data, and may be useful with regard to clinical quality indicators. These indicators are often released centrally, but computed locally in several hospitals. They are typica...

In order to be able to automatically calculate clinical quality indicators, we have proposed CLIF, a stepwise method for clinical quality indicator formalisation. Quality indicators are used for external accountability and hospital comparison. As clinical quality indicators are computed in a decentralised manner by the hospitals themselves, reprodu...

Medical research would benefit from automatic methods that support eligibility evaluation for patient enrollment in clinical trials and design of eligibility criteria. In this study we addressed the problem of formalizing eligibility criteria. By analyzing a large set of breast cancer clinical trials we derived a set of patterns, that capture typic...

To measure the quality of care in order to identify whether and how it can be improved is of increasing importance, and several organisations define quality indicators as tools for such measurement. The values of these quality indicators should ideally be calculated automatically based on data that is being collected during the care process. The ce...

Decision-making, care planning and adaptation of treatment are important aspects of the work of clinicians, that can clearly benefit from IT support. Clinical Practice Guidelines (CPG) languages provide formalisms for specifying knowledge related to such tasks, such as decision criteria and time-oriented aspects of the patient treatment. In these C...

This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that succeed in classifying large ontologies expressed in the tractable OWL 2 EL profile. Reasoners are characterized along several dimensions: The first dimension comprises underlying reasoning characteristics, such as the employed reasoning method and its...

Reasoning is computationally expensive. This is especially true for reasoning on the Web, where data sets are very large and often described by complex terminologies. One way to reduce this complexity is through the use of approximate reasoning methods which trade one computational property (eg. quality of answers) for others, such as time and memo...

This book constitutes the refereed proceedings of the 3rd European Semantic Web Conference, ESWC 2006, held in Budva, Montenegro in June 2006. The 48 revised full papers presented together with abstracts of 3 invited talks were carefully reviewed and selected from a total of 181 submitted papers. The papers are organized in topical sections on onto...

Abstract Many Semantic Web problems are dicult,to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely-coupled peers. We present our divide-conquer-swap strategy and show that this model converges...

The extensive work on Knowledge Engineering in the 1990s has resulted in a systematic analysis of task-types, and the corresponding problem solving methods that can be deployed for different types of tasks. That analysis was the basis for a sound and widely accepted methodology for building knowledge-based systems, and has made it possible to build...

As in software product lifecycle, the effort spent in maintaining medical knowledge in guidelines can be reduced, if modularization, formalization and tracking of domain knowledge are employed across the guideline development phases. We propose to exploit and combine knowledge templates with medical background knowledge from existing thesauri in or...

Modern medical vocabularies can contain up to hundreds of thousands of concepts. In any particular use-case only a small fraction of these will be needed. In this paper we first define two notions of a disease-centric subdomain of a large ontology. We then explore two methods for identifying disease-centric subdomains of such large medical vocabula...

With the emergence of a ubiquitous web of data and services, interoperability between those services without the need for pre-coordination becomes of great importance. However, current web services are often en- gineered in the remote function call style. This imposes very specific interaction patterns on the peers involved, and creates a significa...

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 differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight i...

This paper describes an approach for reasoning about the repairability of workows at design time. We propose a heuristic-based analysis of a workow that aims at evaluating its denition, considering dierent design aspects and characteristics that aect its repairability (called repairability factors), in order to determine if the workow schema suppor...

Medical critiquing systems criticise clinical actions performed by a physician. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of `ideal' actions as described by a clinical guideline. In case differences exist, insight to which extent they are compatible is provided by the critiqui...

Translating clinical guidelines into formal models is beneficial in many ways, but expensive. The progress in medical knowledge requires clinical guidelines to be updated at relatively short intervals, leading to the term living guideline. This causes potentially expensive, frequent updates of the corresponding formal models. When performing these...