Papers by Laszlo Balkanyi
Emerging Infectious Diseases, Apr 1, 2016
Persons, services, goods, capital, and microbes are free to move across borders of the European U... more Persons, services, goods, capital, and microbes are free to move across borders of the European Union (EU), which currently has 28 member states and an estimated population of 508.2 million. The ECDC is an EU agency with a mission to identify, assess, and communicate current and emerging threats to human health posed by infectious diseases. This charge is accomplished through epidemic intelligence, a process to detect, verify, analyze, assess, and investigate events that may represent a threat to public health. These activities are conducted by a team of >10 epidemiologists in the Emergency Operation Center at ECDC. The daily activity of epidemic intelligence at ECDC involves active or automated web searches from confidential and official
Journal of Comparative Effectiveness Research
Aim: Real-world data and real-world evidence (RWE) are becoming more important for healthcare dec... more Aim: Real-world data and real-world evidence (RWE) are becoming more important for healthcare decision making and health technology assessment. We aimed to propose solutions to overcome barriers preventing Central and Eastern European (CEE) countries from using RWE generated in Western Europe. Materials & methods: To achieve this, following a scoping review and a webinar, the most important barriers were selected through a survey. A workshop was held with CEE experts to discuss proposed solutions. Results: Based on survey results, we selected the nine most important barriers. Multiple solutions were proposed, for example, the need for a European consensus, and building trust in using RWE. Conclusion: Through collaboration with regional stakeholders, we proposed a list of solutions to overcome barriers on transferring RWE from Western Europe to CEE countries.
Frontiers in Public Health
BackgroundArtificial intelligence (AI) has attracted much attention because of its enormous poten... more BackgroundArtificial intelligence (AI) has attracted much attention because of its enormous potential in healthcare, but uptake has been slow. There are substantial barriers that challenge health technology assessment (HTA) professionals to use AI-generated evidence for decision-making from large real-world databases (e.g., based on claims data). As part of the European Commission-funded HTx H2020 (Next Generation Health Technology Assessment) project, we aimed to put forward recommendations to support healthcare decision-makers in integrating AI into the HTA processes. The barriers, addressed by the paper, are particularly focusing on Central and Eastern European (CEE) countries, where the implementation of HTA and access to health databases lag behind Western European countries.MethodsWe constructed a survey to rank the barriers to using AI for HTA purposes, completed by respondents from CEE jurisdictions with expertise in HTA. Using the results, two members of the HTx consortium ...
Yearbook of Medical Informatics, 2021
Objectives: The study aims at understanding the structural characteristics and content features o... more Objectives: The study aims at understanding the structural characteristics and content features of COVID-19 literature and public health data from the perspective of the ‘Language and Meaning in Biomedicine’ Working Group (LaMB WG) of IMIA. The LaMB WG has interest in conceptual characteristics, transparency, comparability, and reusability of medical information, both in science and practice. Methods: A set of methods were used (i) investigating the overall speed and dynamics of COVID-19 publications; (ii) characterizing the concepts of COVID-19 (text mining, visualizing a semantic map of related concepts); (iii) assessing (re)usability and combinability of data sets and paper collections (as textual data sets), and checking if information is Findable, Accessible, Interoperable, and Reusable (FAIR). A further method tested practical usability of FAIR requirements by setting up a common data space of epidemiological, virus genetics and governmental public health measures’ stringency ...
Multidiszciplináris Egészség és Jóllét
A cikk szövegbányászati eszközöket mutat be nagy mennyiségű szakirodalom feldolgozására. Megállap... more A cikk szövegbányászati eszközöket mutat be nagy mennyiségű szakirodalom feldolgozására. Megállapítható, hogy jelentős fejlesztések történtek a témában az elmúlt években, és számos, a kutatók által közvetlenül használható eszköz és módszer áll már rendelkezésre. A szerzők a gyermekkori túlsúly és elhízás szakterületének irodalmán mutatnak be 7 módszert, 2 eszköz segítségével (Voyant Tools és VOSViewer), az egyszerűbbtől a bonyolultabbak felé haladva: (1) a vizsgált ún. szövegtestkialakítása, (2) a közlemények számossága, időbeli trendje, (3) a szakkifejezés-gyakoriság elemzése, (4) a kollokáció (együttes előfordulás, együtt-járás) elemzése, (5) korrelációelemzés, (6) kontextuselemzés, (7) fogalomhálózati elemzés, fogalomtérképezés – klaszterezés (csoportosítás). A módszerek és eszkö-zök használatát példákon mutatják be. A módszerek együtt használva feltárják a legfontosabb szakterületi fejleményeket, trendeket. Például azonosítható volt az intervenciók változása az elmúlt tíz évben....
This document set contains three documents:<br> (1) <em>1981-2014 MCR to LaMB sources... more This document set contains three documents:<br> (1) <em>1981-2014 MCR to LaMB sources</em>: a table, listing main events of the working group, called various names but carrying on work in the same are of medical knowledge engineering. The table contains links to the sites where the source documents are stored.<br> (2) <em>2014 LaMB new charter:</em> This document is the new charter of the Working Group, published following the latest name change in 2014 to 'Language and Meaning in Biomedicine'.<br> (3) <em>1984 -2012 MCR history:</em> A short text, describing the history from 1981 to 2012.
Studies in health technology and informatics, 1997
In this paper the authors analyze the main different function types of language in medical enviro... more In this paper the authors analyze the main different function types of language in medical environment in different communicative situations and descriptive tasks. These functions are categorized as knowledge transfer, documentation, directive function, expression of emotions. The computer representation of the information have to be different according to the different tasks. The paper highlights the most important differences and concludes that further research is necessary in the details.
This document set contains the yearly reports and business meetings minutes of the IMIA Working G... more This document set contains the yearly reports and business meetings minutes of the IMIA Working Group 'Language and Meaning in Biomedicine'. The name of the WG was 'Medical Concept Representation' till 2014.
The full content of this workshop, dedicated to coding and language processing is available here:... more The full content of this workshop, dedicated to coding and language processing is available here: <br> Proceedings of a meeting on coding and language processing<br> Methods Inf Med. 1998 Nov;37(4-5):311-575.
This document set contains the bibliography and selected documents of the workshop, Rome, 2005. F... more This document set contains the bibliography and selected documents of the workshop, Rome, 2005. Full <br> proceedings were published in special issue of JBI: Volume 39, Issue 3, Pages 249-378 (June 2006) .
This document set contains a bibliography and selected papers of the IMIA WG 6, 'Medical Conc... more This document set contains a bibliography and selected papers of the IMIA WG 6, 'Medical Concept and Language Representation' 1999 workshop in Phoenix, AZ. The workshop was titled: IMIA WG6 meeting "Terminology and natural language in medicine".
The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – ... more The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – São Paulo,Brazil. This document has all the presentation materials:<br> <br> - Introduction, by Ronald Cornet<br> - From free text to ontology, by Stephane Meystre<br> - Bridging natural and formal languages for representing knowledge and information, by Stefan Schulz<br> - Deep question-answering for biomedical decision support, by Patrick Ruch<br> - Feature extraction for predictive modeling, by Jianying Hu<br> - Connecting structured and unstructured content , by Tomasz Adamusiak<br> - Summary and workshop organization, by Laszlo Balkanyi
This data set combines epidemiological, genetics, and government stringency data of COVID-19 pand... more This data set combines epidemiological, genetics, and government stringency data of COVID-19 pandemics, all from open data sources. The sources are: Our World in Data, Worldometer, GISAID-Nextstrain, and the Oxford COVID-19 Government Response Tracker (OxCGRT). The cut off date of the first version is at the end of June 2020. The simple data set is provided as an Excel workbook, where the first, "readme" worksheet describes the details of data of all the worksheets in the data set. This is a working data set, expected to be refreshed over time. Raw data are not cleaned - this collection is a tool to check various hypotheses regarding possible relations among the various data types. Simple visualisations of data relations are provided in a separate sheet.
This conference paper is about understanding the state of the art in the context of "medical... more This conference paper is about understanding the state of the art in the context of "medical concept representation"<br> It is a descriptive study based on bibliometrics, simple text mining and a social media survey. Results support the general understanding that the focus of research has moved toward medical ontologies, socially active researchers mention the OBO foundry, SNOMED, and UMLS as key resources. Text mining of most cited literature identifies single noun phrases as "health", "information", "clinical", "knowledge", "ontology", "case", "data", " semantic(s)", "concept" and "representation" as leading denominators of the field. Terms as "ontology" and "semantic(s)" .have gained more significance in the last decade.<br> There is a paradigm shift according to both the socially active group of researchers and bibliometric data, comparing...
This paper aims to provide an improved understanding of medical AI and its constituent fields, an... more This paper aims to provide an improved understanding of medical AI and its constituent fields, and their interplay with knowledge representation (KR). We followed a Wittgensteinian approach ("meaning by usage") applied to content metadata labels, using the Medical Subject Headings (MeSH) thesaurus to classify the field. To understand and characterize medical AI and the role of KR, we analyzed: (1) the proportion of papers in MEDLINE related to KR and various AI fields; (2) the interplay among KR and AI fields and overlaps. Authors, chairing the IMIA WG 6, currently called "Language and Meaning in Biomedicine", formerly "Medical Concept Representation" are continuing the tradition of this WG time to time reaching out for a cross-disciplinary overview with other fields of biomedical information science - in this case with AI. Data from over eighty thousand papers showed a steep, six-fold surge in the last 30 years. This growth happened in an escalating an...
The availability of large biomedical datasets brings both new challenges and opportunities. At th... more The availability of large biomedical datasets brings both new challenges and opportunities. At the same time, the resources of biomedical semantics both support the exploitation of these datasets and benefit from them for their own refinement. So the question is neither "What can semantics do for Big Data?", nor "What can Big Data do for semantics?". It is "How can Big Data and biomedical semantics best benefit from each other?". Both the need of processing natural language or structure documents and of building and maintaining semantic resources like lexicons, thesauri, classifications, and ontologies have fueled a broad range of research and development activities in the field of biomedical and health informatics. The workshop explores both extraction and <br> normalization of knowledge from documents and ontology development. This workshop, organized by the IMIA WG LaMB (Language and Meaning in Biomedicine) sees in the advance of Big Data techn...
Studies in Health Technology and Informatics, 2013
This work aims at understanding the state of the art in the broad contextual research area of &qu... more This work aims at understanding the state of the art in the broad contextual research area of "medical concept representation". Our data support the general understanding that the focus of research has moved toward medical ontologies, which we interpret as a paradigm shift. Both the opinion of socially active groups of researchers and changes in bibliometric data since 1988 support this opinion. Socially active researchers mention the OBO foundry, SNOMED CT, and the UMLS as anchor activities.
The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – ... more The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – São Paulo,Brazil. This document set document has (1) all the presentation materials:<br> - Introduction, by Ronald Cornet<br> - From free text to ontology, by Stephane Meystre<br> - Bridging natural and formal languages for representing knowledge and information, by Stefan Schulz<br> - Deep question-answering for biomedical decision support, by Patrick Ruch<br> - Feature extraction for predictive modeling, by Jianying Hu<br> - Connecting structured and unstructured content , by Tomasz Adamusiak<br> - Summary and workshop organization, by Laszlo Balkanyi (2) a reader with a library of references for the MEDINFO 2015 workshop of IMIA LaMB Working Group A related publication (2015 Biom Sem Big Data Workshop Paper) is also available under the 'IMIA LaMB publications' chapter of this repository.
Extracting scientifically accurate terminology from an EU public health regulation is part of the... more Extracting scientifically accurate terminology from an EU public health regulation is part of the knowledge engineering work at the European Centre for Disease Prevention and Control (ECDC). ECDC operates information systems at the crossroads of many areas - posing a challenge for transparency and consistency. Semantic interoperability is based on the Terminology Server (TS). TS value sets (structured vocabularies) describe shared domains as "diseases", "organisms", "public health terms", "geo-entities" "organizations" and "administrative terms" and others. We extracted information from the relevant EC Implementing Decision on case definitions for reporting communicable diseases, listing 53 notifiable infectious diseases, containing clinical, diagnostic, laboratory and epidemiological criteria. We performed a consistency check; a simplification - abstraction; we represented lab criteria in triplets: as 'y' procedura...
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Papers by Laszlo Balkanyi