Semantic representation of reported measurements in radiology

Background In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-text data consists of reports covering the assessment of changes in tumor burden, which are needed for the evaluation of cancer treatment success. Any change of lesion size is a critical factor in follow-up examinations. It is difficult to retrieve specific information from unstructured reports and to compare them over time. Therefore, a prototype was implemented that demonstrates the structured representation of findings, allowing selective review in consecutive examinations and thus more efficient comparison over time. Methods We developed a semantic Model for Clinical Information (MCI) based on existing ontologies from the Open Biological and Biomedical Ontologies (OBO) library. MCI is used for the integrated representation of measured image findings and medical knowledge about the normal size of anatomical entities. An integrated view of the radiology findings is realized by a prototype implementation of a ReportViewer. Further, RECIST (Response Evaluation Criteria In Solid Tumors) guidelines are implemented by SPARQL queries on MCI. The evaluation is based on two data sets of German radiology reports: An oncologic data set consisting of 2584 reports on 377 lymphoma patients and a mixed data set consisting of 6007 reports on diverse medical and surgical patients. All measurement findings were automatically classified as abnormal/normal using formalized medical background knowledge, i.e., knowledge that has been encoded into an ontology. A radiologist evaluated 813 classifications as correct or incorrect. All unclassified findings were evaluated as incorrect. Results The proposed approach allows the automatic classification of findings with an accuracy of 96.4 % for oncologic reports and 92.9 % for mixed reports. The ReportViewer permits efficient comparison of measured findings from consecutive examinations. The implementation of RECIST guidelines with SPARQL enhances the quality of the selection and comparison of target lesions as well as the corresponding treatment response evaluation. Conclusions The developed MCI enables an accurate integrated representation of reported measurements and medical knowledge. Thus, measurements can be automatically classified and integrated in different decision processes. The structured representation is suitable for improved integration of clinical findings during decision-making. The proposed ReportViewer provides a longitudinal overview of the measurements

Mining the Medical and Patent Literature to Support Healthcare and Pharmacovigilance

Recent advancements in healthcare practices and the increasing use of information technology in the medical domain has lead to the rapid generation of free-text data in forms of scientific articles, e-health records, patents, and document inventories. This has urged the development of sophisticated information retrieval and information extraction technologies. A fundamental requirement for the automatic processing of biomedical text is the identification of information carrying units such as the concepts or named entities. In this context, this work focuses on the identification of medical disorders (such as diseases and adverse effects) which denote an important category of concepts in the medical text. Two methodologies were investigated in this regard and they are dictionary-based and machine learning-based approaches. Futhermore, the capabilities of the concept recognition techniques were systematically exploited to build a semantic search platform for the retrieval of e-health records and patents. The system facilitates conventional text search as well as semantic and ontological searches. Performance of the adapted retrieval platform for e-health records and patents was evaluated within open assessment challenges (i.e. TRECMED and TRECCHEM respectively) wherein the system was best rated in comparison to several other competing information retrieval platforms. Finally, from the medico-pharma perspective, a strategy for the identification of adverse drug events from medical case reports was developed. Qualitative evaluation as well as an expert validation of the developed system's performance showed robust results. In conclusion, this thesis presents approaches for efficient information retrieval and information extraction from various biomedical literature sources in the support of healthcare and pharmacovigilance. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. The applied strategies have potential to enhance the literature-searches performed by biomedical, healthcare, and patent professionals. This can promote the literature-based knowledge discovery, improve the safety and effectiveness of medical practices, and drive the research and development in medical and healthcare arena

Improving literature searching in systematic reviews: the application of tailored literature searching compared to ‘the conventional approach’

Background Literature searching is acknowledged as a crucial step in a systematic review. Information professionals, in response to the needs of intervention effectiveness systematic reviews, have developed a systematic process of literature searching which aims to be comprehensive, transparent and reproducible, and to minimise the introduction of bias in systematic reviews. The process which has evolved has not been examined in detail before but it has been adopted as the principal approach to literature searching in other types of systematic review. It is not clear if this is appropriate and if an alternative approach might be more effective. Thesis aims The aims of this thesis are to: 1) examine approaches to systematic literature searching for systematic reviews; and 2) propose and test a method of systematic literature searching for reviews which do not focus on the effectiveness of clinical interventions. Methods Two literature reviews, one systematic review and two comparative case studies were undertaken to meet the aims of the thesis. Results A critical literature review identified and described a conventional approach to literature searching common to nine leading handbooks of systematic review. An alternative, tailored approach to literature searching was developed. Two case studies illustrated that the tailored approach was more effective, and potentially offered better value, than the conventional approach. Conclusions Information professionals can develop tailored literature search approaches for use in systematic reviews and as a useful alternative to the conventional approach, particularly for reviews including study designs beyond controlled trials. The role of the information professional as decision maker, the involvement of the research team and experts, preparing for literature searching and the use of supplementary search methods, are important to the success of tailored literature search approaches

Clinical foundations and information architecture for the implementation of a federated health record service

Clinical care increasingly requires healthcare professionals to access patient record information that may be distributed across multiple sites, held in a variety of paper and electronic formats, and represented as mixtures of narrative, structured, coded and multi-media entries. A longitudinal person-centred electronic health record (EHR) is a much-anticipated solution to this problem, but its realisation is proving to be a long and complex journey. This Thesis explores the history and evolution of clinical information systems, and establishes a set of clinical and ethico-legal requirements for a generic EHR server. A federation approach (FHR) to harmonising distributed heterogeneous electronic clinical databases is advocated as the basis for meeting these requirements. A set of information models and middleware services, needed to implement a Federated Health Record server, are then described, thereby supporting access by clinical applications to a distributed set of feeder systems holding patient record information. The overall information architecture thus defined provides a generic means of combining such feeder system data to create a virtual electronic health record. Active collaboration in a wide range of clinical contexts, across the whole of Europe, has been central to the evolution of the approach taken. A federated health record server based on this architecture has been implemented by the author and colleagues and deployed in a live clinical environment in the Department of Cardiovascular Medicine at the Whittington Hospital in North London. This implementation experience has fed back into the conceptual development of the approach and has provided "proof-of-concept" verification of its completeness and practical utility. This research has benefited from collaboration with a wide range of healthcare sites, informatics organisations and industry across Europe though several EU Health Telematics projects: GEHR, Synapses, EHCR-SupA, SynEx, Medicate and 6WINIT. The information models published here have been placed in the public domain and have substantially contributed to two generations of CEN health informatics standards, including CEN TC/251 ENV 13606

Resource discovery in heterogeneous digital content environments

The concept of 'resource discovery' is central to our understanding of how users explore, navigate, locate and retrieve information resources. This submission for a PhD by Published Works examines a series of 11 related works which explore topics pertaining to resource discovery, each demonstrating heterogeneity in their digital discovery context. The assembled works are prefaced by nine chapters which seek to review and critically analyse the contribution of each work, as well as provide contextualization within the wider body of research literature. A series of conceptual sub-themes is used to organize and structure the works and the accompanying critical commentary. The thesis first begins by examining issues in distributed discovery contexts by studying collection level metadata (CLM), its application in 'information landscaping' techniques, and its relationship to the efficacy of federated item-level search tools. This research narrative continues but expands in the later works and commentary to consider the application of Knowledge Organization Systems (KOS), particularly within Semantic Web and machine interface contexts, with investigations of semantically aware terminology services in distributed discovery. The necessary modelling of data structures to support resource discovery - and its associated functionalities within digital libraries and repositories - is then considered within the novel context of technology-supported curriculum design repositories, where questions of human-computer interaction (HCI) are also examined. The final works studied as part of the thesis are those which investigate and evaluate the efficacy of open repositories in exposing knowledge commons to resource discovery via web search agents. Through the analysis of the collected works it is possible to identify a unifying theory of resource discovery, with the proposed concept of (meta)data alignment described and presented with a visual model. This analysis assists in the identification of a number of research topics worthy of further research; but it also highlights an incremental transition by the present author, from using research to inform the development of technologies designed to support or facilitate resource discovery, particularly at a 'meta' level, to the application of specific technologies to address resource discovery issues in a local context. Despite this variation the research narrative has remained focussed on topics surrounding resource discovery in heterogeneous digital content environments and is noted as having generated a coherent body of work. Separate chapters are used to consider the methodological approaches adopted in each work and the contribution made to research knowledge and professional practice.The concept of 'resource discovery' is central to our understanding of how users explore, navigate, locate and retrieve information resources. This submission for a PhD by Published Works examines a series of 11 related works which explore topics pertaining to resource discovery, each demonstrating heterogeneity in their digital discovery context. The assembled works are prefaced by nine chapters which seek to review and critically analyse the contribution of each work, as well as provide contextualization within the wider body of research literature. A series of conceptual sub-themes is used to organize and structure the works and the accompanying critical commentary. The thesis first begins by examining issues in distributed discovery contexts by studying collection level metadata (CLM), its application in 'information landscaping' techniques, and its relationship to the efficacy of federated item-level search tools. This research narrative continues but expands in the later works and commentary to consider the application of Knowledge Organization Systems (KOS), particularly within Semantic Web and machine interface contexts, with investigations of semantically aware terminology services in distributed discovery. The necessary modelling of data structures to support resource discovery - and its associated functionalities within digital libraries and repositories - is then considered within the novel context of technology-supported curriculum design repositories, where questions of human-computer interaction (HCI) are also examined. The final works studied as part of the thesis are those which investigate and evaluate the efficacy of open repositories in exposing knowledge commons to resource discovery via web search agents. Through the analysis of the collected works it is possible to identify a unifying theory of resource discovery, with the proposed concept of (meta)data alignment described and presented with a visual model. This analysis assists in the identification of a number of research topics worthy of further research; but it also highlights an incremental transition by the present author, from using research to inform the development of technologies designed to support or facilitate resource discovery, particularly at a 'meta' level, to the application of specific technologies to address resource discovery issues in a local context. Despite this variation the research narrative has remained focussed on topics surrounding resource discovery in heterogeneous digital content environments and is noted as having generated a coherent body of work. Separate chapters are used to consider the methodological approaches adopted in each work and the contribution made to research knowledge and professional practice

Copy number variants on chromosome X and impact in neurodevelopment disorders

Introdução: Variações do número de cópias (CNV) no cromossoma X estão associadas a diversas doenças, nomeadamente perturbações no neurodesenvolvimento. Várias regiões suscetíveis de doença foram identificadas no cromossoma X, alguns já associados a síndromes genéticos conhecidos, outros carecem de identificação. Array comparative genomic hybridization (aCGH) é um método útil pra identificar CNVs patogénicos ou provavelmente patogénicos num grupo de doentes. O objetivo principal deste estudo é mostrar uma correlação entre o genótipo e o fenótipo em CNVs presentes no cromossoma X. Métodos: O estudo utilizou a base de dados de aCGH do Departamento de Genética da Faculdade de Medicina e os registos clínicos de dois hospitais. Doentes com CNVs patogénicos ou provavelmente patogénicos no cromossoma X foram incluídos no estudo. Bases de dados e literatura relacionada foram usados para uma melhor compreensão da corrleção genótipo-fenótipo. Resultados: De 2852 doentes estudados com recurso à técnica de aCGH, em 42 foram identificados CNVs clinicamente relevantes no cromossoma X: 47,62% foram classificados como provavelmente patogénico e 52,38% como patogénicos. Os 20 pacientes classificados como provavelmente patogénicos: 5% são referentes a material prenatal, enquanto 95% foi realizado no contexto pós-natal. Relativamente aos 22 CNVs patogénicos, 41% são relativos a casos pré-natais enquanto 59% são pós-natais. As regiões cromossómicas Xp22.31, Xp22.32 e Xq28 são as que mais frequentemente apresentam CNVs. As regiões Xp11.22, Xp11.3 e Xq11.2 também mostraram diversos CNVs relevantes. Conclusões: Com este estudo, contribuímos para uma melhor compreensão dos CNVs associados a patologia no cromossoma X, especialmente aqueles relacionados com perturbações do neurodesenvolvimento, permitindo um diagnóstico mais preciso, melhorando o aconselhamento genético, especialmente no diagnóstico pré-natal.Introduction: Copy number variants (CNVs) on X chromosome are associated with several human diseases, especially impairment of the neurodevelopment. Several disease susceptibility regions have been identified on X chromosome, some already associated with known genetic syndromes, nonetheless others remain to be clarified. Array comparative genomic hybridization (aCGH) is a useful method to access pathogenic or likely-pathogenic CNVs in a clinical population. The main goal of this study was to provide a genotype-phenotype correlation focused on CNVs present on the X chromosome. Methods: A cross-sectional study was performed using the aCGH database of the Genetic Department of the Faculty of Medicine and clinical records from hospitals database. Patients with pathogenic or likely pathogenic CNVs on chromosome X were included in the study. Databases and related literature were used for a better understanding of the genotypephenotype correlation. Results: From 2852 patients studied using aCGH, 42 presented clinically relevant CNVs on X chromosome: 47,62% were classified as likely pathogenic and 52,38% as pathogenic. Among the 20 likely pathogenic CNVs, 5% were identified in the prenatal context, while 95% were postnatal. Concerning to the 22 pathogenic CNVs, 41% were prenatal cases and 59% were postnatal cases. Chromosomal regions Xp22.31, Xp22.32 and Xq28 exhibited a higher incidence of CNVs. Frequently Xp11.22, Xp11.3 and Xq11.2 regions showed clinically relevant CNVs. Conclusions: We contributed for a better understanding of the disease-associated CNVs on the X chromosome, especially those related with neurodevelopment disorders, allowing a more accurate diagnosis, improving genetic counseling namely in prenatal diagnosis setting