Publications by authors named "Casimir A Kulikowski"

26 Publications

  • Page 1 of 1

Pandemics: Historically Slow "Learning Curve" Leading to Biomedical Informatics and Vaccine Breakthroughs.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Department of Computer Science, Rutgers University, USA.

Background: The worldwide tragedy of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic vividly demonstrates just how inadequate mitigation and control of the spread of infectious diseases can be when faced with a new microorganism with unknown pathogenic effects. Responses by governments in charge of public health, and all other involved organizations, have proved largely wanting. Data infrastructure and the information and communication systems needed to deal with the pandemic have likewise not been up to the task. Nevertheless, after a year of the worldwide outbreak, hope arises from this being the first major pandemic event in history where genomic and related biosciences - relying on biomedical informatics - have been essential in decoding the viral sequence data and producing the mRNA and other biotechnologies that unexpectedly rapidly have led to investigation, design, development, and testing of useful vaccines. Medical informatics may also help support public health actions and clinical interventions - but scalability and impact will depend on overcoming ingrained human shortcomings to deal with complex socio-economic, political, and technological disruptions together with the many ethical challenges presented by pandemics.

Objectives: The principal goal is to review the history of biomedical information and healthcare practices related to past pandemics in order to illustrate just how exceptional and dependent on biomedical informatics are the recent scientific insights into human immune responses to viral infection, which are enabling rapid antiviral vaccine development and clinical management of severe cases - despite the many societal challenges ahead.

Methods: This paper briefly reviews some of the key historical antecedents leading up to modern insights into epidemic and pandemic processes with their biomedical and healthcare information intended to guide practitioners, agencies, and the lay public in today's ongoing pandemic events.

Conclusions: Poor scientific understanding and excessively slow learning about infectious disease processes and mitigating behaviors have stymied effective treatment until the present time. Advances in insights about immune systems, genomes, proteomes, and all the other -omes, became a reality thanks to the key sequencing technologies and biomedical informatics that enabled the Human Genome Project, and only now, 20 years later, are having an impact in ameliorating devastating zoonotic infectious pandemics, including the present SARS-CoV-2 event through unprecedently rapid vaccine development. In the future these advances will hopefully also enable more targeted prevention and treatment of disease. However, past and present shortcomings of most of the COVID-19 pandemic responses illustrate just how difficult it is to persuade enough people - and especially political leaders - to adopt societally beneficial risk-avoidance behaviors and policies, even as these become better understood.
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http://dx.doi.org/10.1055/s-0041-1726482DOI Listing
April 2021

Evolution of Interdisciplinarity in Medical Informatics in Europe: Patterns from Intertwining Histories.

Stud Health Technol Inform 2020 Jun;270:1113-1117

Victor Babes University of Medicine and Pharmacy, Timisoara, Romania.

The IMIA History project book we are co-editing with colleagues from the IMIA History Working Group includes histories of early contributions to medical and healthcare informatics, as described by a sample of pioneers and experts, detailing how their own ideas developed from their work on various topics in the field at the beginnings of their contributions to the field. Its contents serve as a preliminary guide for meta-analyses of how the different contributors state their personal interdisciplinary origins from today's perspectives. In this short article we provide a brief preview of how an analysis of disciplinary characteristics from individual histories can begin to shed light on processes of interdisciplinary evolution of medical informatics in Europe.
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http://dx.doi.org/10.3233/SHTI200335DOI Listing
June 2020

Donald A. B. Lindberg: Inspiring Leader and Visionary in Biomedicine, Healthcare, and Informatics.

Yearb Med Inform 2020 Aug 17;29(1):253-258. Epub 2020 Apr 17.

Department of Computer Science, Rutgers University, USA.

Background: As Director of the US National Library of Medicine (NLM) for 30 years, Dr. Donald A. B. Lindberg was instrumental in bringing biomedical research and healthcare worldwide into the age of genomic and translational medicine through the informatics systems developed by the NLM. Lindberg opened free access and worldwide public dissemination of all the NLM's biomedical literature and databases, thus helping transform not only biomedical research like the Human Genome Project and its successors, but also the practices of medicine and healthcare internationally. Guiding, leading, and teaching-by-example at national, regional, and global levels of biomedical and healthcare informatics, Lindberg helped coalesce a dynamic discipline that provides a foundation for the human understanding which promotes the future health of our world.

Objectives: To provide historical insight into the scientific, technological, and practical clinical accomplishments of Donald Lindberg, and to describe how this led to contributions in the worldwide interdisciplinary evolution of informatics, and its impact on the biosciences and practices of medicine, nursing, and other healthcare-related disciplines.

Methods: Review and comment on the publications, scientific contributions, and leadership of Donald Lindberg in the evolution of biomedical and health informatics which anticipate the vision, scholarship, research in the field, and represent the deeply ethical humanism he exhibited throughout his life. These were essential in producing the informatics systems, such as the Unified Medical Language System (UMLS), MEDLINE, PubMed, PubMed Central, and ClinicalTrials.gov, which, together with NLM training programs and conferences, made possible the interactions among researchers and practitioners leading to the past quarter-century of rapid and dramatic advances in biomedical scientific inquiry and clinical discoveries, openly shared across the globe.

Conclusion: Dr. Lindberg was a uniquely talented physician and pioneering researcher in biomedical and health informatics. As the main leader in developing and funding innovative informatics research for more than 30 years as Director of the National Library of Medicine, he helped bring together the most creative interdisciplinary researchers to bridge the worlds of biomedical research, education, and clinical practice. Lindberg's emphasis on open-access to the biomedical literature through publicly shared computer-mediated methods of search and inquiry are seen as an example of ethical scientific openness.
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http://dx.doi.org/10.1055/s-0040-1701972DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442506PMC
August 2020

Roots of Interdisciplinarity in European Medical Informatics.

Stud Health Technol Inform 2019 Jul;262:146-149

Rutgers University, Piscataway, NJ, USA.

The roots of interdisciplinary of medical informatics are sought through the analysis of the themes approached by the pioneers of this field. The data included in the study comes mostly from "personal stories" of European these scientists collected by IMIA WG History as well as from some biographical notes. Most researchers came from the technical-scientific field, but the double specialization was very common. The proportions of the main topic approaches are discussed. The roots of medical informatics interdisciplinary were formed during the pioneering period, when most major concepts and chapters of medical informatics took contour.
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http://dx.doi.org/10.3233/SHTI190038DOI Listing
July 2019

Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art - with Reflections on Present AIM Challenges.

Yearb Med Inform 2019 Aug 25;28(1):249-256. Epub 2019 Apr 25.

Department of Computer Science, Rutgers University, USA.

Background: The rise of biomedical expert heuristic knowledge-based approaches for computational modeling and problem solving, for scientific inquiry and medical decision-making, and for consultation in the 1970's led to a major change in the paradigm that affected all of artificial intelligence (AI) research. Since then, AI has evolved, surviving several "winters", as it has oscillated between relying on expensive and hard-to-validate knowledge-based approaches, and the alternative of using machine learning methods for inferring classification rules from labelled datasets. In the past couple of decades, we are seeing a gradual but progressive intertwining of the two.

Objectives: To give an overview of early directions in AI in medicine and threads of some subsequent developments motivated by the very different goals of scientific inquiry for biomedical research, and for computational modeling of clinical reasoning and more general healthcare problem solving from the perspective of today's "AI-Deep Learning Boom". To show how, from the beginning, AI was central to Biomedical and Health Informatics (BMHI), as a field investigating how to understand intelligent thinking in dealing professionally with the practice for healthcare, developing mathematical models, technology, and software tools to aid human experts in biomedicine, despite many previous bouts of "exuberant optimism" about the methodologies deployed.

Methods: An overview and commentary on some of the early research and publications in AI in biomedicine, emphasizing the different approaches to the modeling of problems involved in clinical practice in contrast to those of biomedical science. A concluding reflection of a few current challenges and pitfalls of AI in some biomedical applications.

Conclusion: While biomedical knowledge-based systems played a critical role in influencing AI in its early days, 50 years later they have taken a back seat behind "Deep Learning" which promises to discover knowledge structures for inference and prediction, both in science and for clinical decision-support. Early work on AI for medical consultation turned out to be more useful for explanation and teaching than for clinical practice, as had been originally intended. Today, despite the many reported successes of deep learning, fundamental scientific challenges arise in drawing on models of brain science, cognition, and language, if AI is to augment and complement rather than replace human judgment and expertise in biomedicine while also incorporating these advances for translational medicine. Understanding clinical phenotypes and how they relate to precision and personalization of care requires not only scientific inquiry, but also humanistic models of treatment that respond to patient and practitioner narrative exchanges, since it is the stories and insights of human experts which encourage what Norbert Weiner termed the ethical "human use of human beings", so central to adherence to the Hippocratic Oath.
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http://dx.doi.org/10.1055/s-0039-1677895DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697545PMC
August 2019

50th Anniversary International Medical Informatics Association (IMIA) History Working Group and Its Projects.

Stud Health Technol Inform 2017 ;245:758-762

College of Nursing, Seoul National University, Seoul, Korea.

The IMIA History Working Group has as its first goal the editing of a volume of contributions from pioneers and leaders in the field of biomedical and health informatics (BMHI) to commemorate the 50th anniversary of IMIA's predecessor IFIP-TC4. This paper describes how the IMIA History WG evolved from an earlier Taskforce, and has focused on producing the edited book of original contributions. We describe its proposed outline of objectives for the personal stories, and national and regional society narratives, together with some comments on the evolution of Medinfo meeting contributions over the years, to provide a reference source for the early motivations of the scientific, clinical, educational, and professional changes that have influenced the historical course of our field.
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June 2018

Decision-Tree Model for Support of Health Policy Choices Based on Pneumococcal Conjugate Vaccine (PCV) Program Outcomes.

Stud Health Technol Inform 2017 ;245:40-44

Merck Research Laboratories, Rahway, New Jersey, USA.

Pneumococcal Conjugate Vaccine (PCV) has the potential to save lives in low-income countries. We have developed a computational model and web-based decision support software for comparing cost-benefit tradeoffs from alternative PCV program designs, considering their direct and indirect effects on early childhood populations in resource-poor settings. This supports policy-makers in estimating potential health outcomes and cost-effectiveness of different vaccination program strategies for a wide range of population coverage and vaccine effectiveness assumptions.
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June 2018

Impact of prostate biopsy tumor amount on imaging based prognostics employing transductive semi-supervised regression.

Annu Int Conf IEEE Eng Med Biol Soc 2016 Aug;2016:5604-5607

For newly diagnosed prostate cancer patients with a positive biopsy, there are a variety of treatment options to consider. To aid physicians and patients in their decision making, a variety of predictive assays have emerged within the last decade, many of them imaging based. These assays build predictive models for survival analysis to provide personalized risk assessments for the patients. However, there have rarely been any published studies on how the amount of tumor in the positive prostate biopsy affects the predictive power of these imaging based assays. Recently we have proposed a new algorithmic framework for survival analysis employing semi-supervised transductive regression. This approach has improved the predictive power of biopsy based prostate cancer prognostic models. In this paper, we explore how different amounts of tumor in the prostate biopsy affect the accuracy of imaging based prognostic models employing this framework. We show that the framework improves accuracy even with diminishing amounts of tumor, thereby enabling more accurate treatment decisions.
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http://dx.doi.org/10.1109/EMBC.2016.7591997DOI Listing
August 2016

Research Strategies for Biomedical and Health Informatics. Some Thought-provoking and Critical Proposals to Encourage Scientific Debate on the Nature of Good Research in Medical Informatics.

Methods Inf Med 2017 Jan 25;56(S 01):e1-e10. Epub 2017 Jan 25.

Background: Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate.

Objectives: To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education?

Methods: Outstanding informatics scientists were invited to three panel sessions on this topic in leading international conferences (MIE 2015, Medinfo 2015, HEC 2016) in order to get their answers to these questions.

Results: A variety of themes emerged in the set of answers provided by the panellists. Some panellists took the theoretical foundations of the field for granted, while several questioned whether the field was actually grounded in a strong theoretical foundation. Panellists proposed a range of suggestions for new or improved approaches, methodologies, and techniques to enhance the BMHI research agenda.

Conclusions: The field of BMHI is on the one hand maturing as an academic community and intellectual endeavour. On the other hand vendor-supplied solutions may be too readily and uncritically accepted in health care practice. There is a high chance that BMHI will continue to flourish as an important discipline; its innovative interventions might then reach the original objectives of advancing science and improving health care outcomes.
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http://dx.doi.org/10.3414/ME16-01-0125DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388922PMC
January 2017

Discussion of "The New Role of Biomedical Informatics in the Age of Digital Medicine".

Methods Inf Med 2016 Oct 15;55(5):403-421. Epub 2016 Aug 15.

Najeeb Al-Shorbaji, Vice-President for Knowledge, Research, and Ethics, e-Marefa (www.e-marefa.net), P.O. Box 2351, Amman 11953, Jordan, E-mail:

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "The New Role of Biomedical Informatics in the Age of Digital Medicine" written by Fernando J. Martin-Sanchez and Guillermo H. Lopez-Campos [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Martin-Sanchez and Lopez-Campos. In subsequent issues the discussion can continue through letters to the editor.
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http://dx.doi.org/10.3414/ME15-12-0005DOI Listing
October 2016

A method for exploring implicit concept relatedness in biomedical knowledge network.

BMC Bioinformatics 2016 Jul 19;17 Suppl 9:265. Epub 2016 Jul 19.

College of Computer Science and Technology, Jilin Univesity, 2699 Qianjin St, Changchun, China.

Background: Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community.

Results: In this study, a hybrid biomedical knowledge network is constructed by linking concepts across multiple biomedical ontologies as well as non-structural biomedical knowledge sources. To discover implicit relatedness between concepts in ontologies for which potentially valuable relationships (implicit knowledge) may exist, we developed a Multi-Ontology Relatedness Model (MORM) within the knowledge network, for which a relatedness network (RN) is defined and computed across multiple ontologies using a formal inference mechanism of set-theoretic operations. Semantic constraints are designed and implemented to prune the search space of the relatedness network.

Conclusions: Experiments to test examples of several biomedical applications have been carried out, and the evaluation of the results showed an encouraging potential of the proposed approach to biomedical knowledge discovery.
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http://dx.doi.org/10.1186/s12859-016-1131-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959351PMC
July 2016

Discussion of "Computational Electrocardiography: Revisiting Holter ECG Monitoring".

Methods Inf Med 2016 Aug 13;55(4):312-21. Epub 2016 Jul 13.

Herbert Witte, Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich-Schiller University, Bachstraße 18, 07743 Jena, E-mail:

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Computational Electrocardiography: Revisiting Holter ECG Monitoring" written by Thomas M. Deserno and Nikolaus Marx. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Deserno and Marx. In subsequent issues the discussion can continue through letters to the editor.
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http://dx.doi.org/10.3414/ME15-15-0009DOI Listing
August 2016

Social Media as Catalyzer for Connected Health: Hype or Hope? Perspectives from IMIA Working Groups.

Stud Health Technol Inform 2016 ;225:602-4

Rutgers - The State University of New Jersey, New Brunswick, NJ, USA, IMIA History in Biomedical and Health Informatics WG,

The Internet and social media are becoming ubiquitous technologies that are transforming the health sector. Social media has become an avenue for accessing, creating and sharing health information among patients and healthcare professionals. Furthermore, social media has become a key feature in many eHealth solutions, including wearable technologies, Big Data solutions, eLearning systems, Serious Games, Medical imaging, etc. These hyper-connected technologies are facilitating a paradigm shift towards more connected health. In this panel, representatives of different IMIA Working Groups will explore how both hope and hype contribute to social media's catalyzing role in creating connected health solutions.
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April 2017

The 50(th) Anniversary IMIA History of Medical Informatics Project.

Acta Inform Med 2014 Feb 25;22(1):68-70. Epub 2014 Jan 25.

Department of Computer Science, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.

At the meeting of the IMIA Board in 2009 in Hiroshima, it approved an IMIA 50th Anniversary History Project to produce a historical volume and other materials to commemorate the anniversary of the foundation of the predecessor of IMIA-the IFIP-TC4 in 1967. A Taskforce was organized under the direction of Casimir Kulikowski, then the VP for Services of IMIA, and since that time it has met regularly to plan and implement the 50th Anniversary History of IMIA as an edited volume, and as material available online on a Media Presentation Database. The IMIA Taskforce is gathering IMIA-related archival materials, currently accessible through a prototype media repository at Rutgers University in order to help those contributing to the book or writing their own recollections and histories. The materials will support a chronicle of the development and evolution of IMIA, its contributors, its sponsored events and publications, educational and other professional activities. During 2013 Workshops were held at the Prague EFMI-STC meeting in April and at the MEDINFO 2013 Congress in Copenhagen in August.
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http://dx.doi.org/10.5455/aim.2014.22.68-70DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947943PMC
February 2014

An informatics approach to chronicling the history of IMIA.

Stud Health Technol Inform 2013 ;192:1130

Department of Computer Science, Rutgers - The State University of New Jersey, Piscataway, NJ, USA.

With the 50th Anniversary of IMIA approaching in 2017, the IMIA Board approved the creation of a Taskforce for compiling materials and writing a history of the organization. As part of the work of the Taskforce, the authors have developed informatics tools, and begun collecting IMIA-related historical materials from its members, while soliciting participation and contributions from those involved in the early days of the organization and its predecessor IFIP-TC4. This poster describes the structure and preliminary contents of the media mining and presentation tools designed at Rutgers University for use by the IMIA History Editorial Board, being constituted to produce the 50th Anniversary publication, as well as an online archive of materials chronicling the evolution of IMIA. A major feature of the data repository is its ability to present different modalities of textual, visual and graphical (timelines, trends) summarizations for the IMIA document collection. It will be augmented with audio material, and will serve as an archival repository for historical research, including software tools for text analysis and extraction of the information entering into the 50th Anniversary volume.
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April 2015

Note on Friedman's 'what informatics is and isn't'.

J Am Med Inform Assoc 2013 Dec 16;20(e2):e365-6. Epub 2013 Apr 16.

Biomedical Informatics Group, Universidad Politecnica de Madrid, Madrid, Spain.

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http://dx.doi.org/10.1136/amiajnl-2013-001807DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3861923PMC
December 2013

AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline.

J Am Med Inform Assoc 2012 Nov-Dec;19(6):931-8. Epub 2012 Jun 8.

Department of Computer Science, Rutgers University, New Brunswick, New Jersey, USA.

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is 'the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.' Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine. The shared core informatics competencies of BMI draw on the practical experience of many specific informatics sub-disciplines. The AMIA BMI analysis highlights the central shared set of competencies that should guide curriculum design and that graduate students should be expected to master.
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http://dx.doi.org/10.1136/amiajnl-2012-001053DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3534470PMC
April 2013

Towards health informatics 3.0. Editorial.

Yearb Med Inform 2011 ;6:6-7

Objectives: To provide an editorial introduction to the 2011 IMIA Yearbook of Medical Informatics with an overview of its contents and contributors.

Methods: A brief overview of the main theme, and an outline of the purposes, contents, format, and acknowledgment of contributions for the 2011 IMIA Yearbook.

Results: This 2011 issue of the IMIA Yearbook highlights important developments in the development of Web 3.0 capabilities that are increasing in Health Informatics, impacting the activities in research, education and practice in this interdisciplinary field. There has been steady progress towards introducing semantics into informatics systems through more sophisticated representations of knowledge in their underlying information. Health Informatics 3.0 capabilities are identified from the recent literature, illustrated by selected papers published during the past 12 months, and articles reported by IMIA Working Groups.

Conclusion: Surveys of the main research sub-fields in biomedical informatics in the Yearbook provide an overview of progress and current challenges across the spectrum of the discipline, focusing on Web 3.0 challenges and opportunities.
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January 2014

Ortholog clustering on a multipartite graph.

IEEE/ACM Trans Comput Biol Bioinform 2007 Jan-Mar;4(1):17-27

Department of Computer Science, Rutgers-The State University of New Jersey, Piscataway 08854, USA.

We present a method for automatically extracting groups of orthologous genes from a large set of genomes by a new clustering algorithm on a weighted multipartite graph. The method assigns a score to an arbitrary subset of genes from multiple genomes to assess the orthologous relationships between genes in the subset. This score is computed using sequence similarities between the member genes and the phylogenetic relationship between the corresponding genomes. An ortholog cluster is found as the subset with the highest score, so ortholog clustering is formulated as a combinatorial optimization problem. The algorithm for finding an ortholog cluster runs in time O(absolute value(E) + absolute value(V) log absolute value(V)), where V and E are the sets of vertices and edges, respectively, in the graph. However, if we discretize the similarity scores into a constant number of bins, the runtime improves to O(absolute value(E) + absolute value(V)). The proposed method was applied to seven complete eukaryote genomes on which the manually curated database of eukaryotic ortholog clusters, KOG, is constructed. A comparison of our results with the manually curated ortholog clusters shows that our clusters are well correlated with the existing clusters.
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http://dx.doi.org/10.1109/TCBB.2007.1004DOI Listing
April 2007

Prediction in annotation based guideline encoding.

AMIA Annu Symp Proc 2006 :314-8

University of Medicine and Dentistry of New Jersey, New Brunswick, NJ, USA.

The encoding of clinical practice guidelines into machine operable representations poses numerous challenges and will require considerable human intervention for the foreseeable future. To assist and potentially speed up this process, we have developed an incremental approach to guideline encoding which begins with the annotation of the original guideline text using markup techniques. A modular and flexible sequence of subtasks results in increasingly inter-operable representations while maintaining the connections to all prior source representations and supporting knowledge. To reduce the encoding bottleneck we also employ a number of machine-assisted learning and prediction techniques within a knowledge-based software environment. Promising results with a straightforward incremental learning algorithm illustrate the feasibility of such an approach.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839750PMC
September 2007

Reflections on biomedical informatics: from cybernetics to genomic medicine and nanomedicine.

Stud Health Technol Inform 2006 ;124:19-24

Biomedical Informatics Group, Artificial Intelligence Lab, Universidad Politecnica de Madrid, Spain.

Expanding on our previous analysis of Biomedical Informatics (BMI), the present perspective ranges from cybernetics to nanomedicine, based on its scientific, historical, philosophical, theoretical, experimental, and technological aspects as they affect systems developments, simulation and modelling, education, and the impact on healthcare. We then suggest that BMI is still searching for strong basic scientific principles around which it can crystallize. As -omic biological knowledge increasingly impacts the future of medicine, ubiquitous computing and informatics become even more essential, not only for the technological infrastructure, but as a part of the scientific enterprise itself. The Virtual Physiological Human and investigations into nanomedicine will surely produce yet more unpredictable opportunities, leading to significant changes in biomedical research and practice. As a discipline involved in making such advances possible, BMI is likely to need to re-define itself and extend its research horizons to meet the new challenges.
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January 2007

Vocabulary requirements for implementing clinical guidelines in an electronic medical record: a case study.

AMIA Annu Symp Proc 2005 :709-13

University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, USA.

As part of a larger effort to automate guidelines we determined the number and types of clinical variables required to implement two complex clinical guidelines and the adequacy of the electronic medical record (EMR) to capture them. 178 unique variables were required by both guidelines. Variables were classified as simple (existing observation terms in the EMR), calculated (transformations of simple variables), and complex (requiring multiple simple variables and logical rules for combining them). Many variables are unlikely to be instantiated in an EMR without focused efforts to collect them. In addition, many variables required knowledge that was neither provided in the guideline nor referenced. We conclude that, although the EMR contains the necessary variables to implement these guidelines, successful automated implementation requires unambiguous definition of required terms, incorporation of additional knowledge not provided in the guideline and modification of workflow to collect variables not normally captured in routine clinical care.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1560696PMC
February 2007

Bioinformatics and medical informatics: collaborations on the road to genomic medicine?

J Am Med Inform Assoc 2003 Nov-Dec;10(6):515-22. Epub 2003 Aug 4.

Medical Informatics Group, Artificial Intelligence Laboratory, Universidad Politécnica de Madrid, Spain.

In this report, the authors compare and contrast medical informatics (MI) and bioinformatics (BI) and provide a viewpoint on their complementarities and potential for collaboration in various subfields. The authors compare MI and BI along several dimensions, including: (1) historical development of the disciplines, (2) their scientific foundations, (3) data quality and analysis, (4) integration of knowledge and databases, (5) informatics tools to support practice, (6) informatics methods to support research (signal processing, imaging and vision, and computational modeling, (7) professional and patient continuing education, and (8) education and training. It is pointed out that, while the two disciplines differ in their histories, scientific foundations, and methodologic approaches to research in various areas, they nevertheless share methods and tools, which provides a basis for exchange of experience in their different applications. MI expertise in developing health care applications and the strength of BI in biological "discovery science" complement each other well. The new field of biomedical informatics (BMI) holds great promise for developing informatics methods that will be crucial in the development of genomic medicine. The future of BMI will be influenced strongly by whether significant advances in clinical practice and biomedical research come about from separate efforts in MI and BI, or from emerging, hybrid informatics subdisciplines at their interface.
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http://dx.doi.org/10.1197/jamia.M1305DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC264428PMC
December 2003