A scientific mind embraces medicine: Donald Lindberg's education and early career.

As a young pathologist, Donald A.B. Lindberg, M.D., tirelessly sought scientific solutions to clinical and research problems. Directing several clinical laboratories at the University of Missouri in Columbia, Dr. Lindberg developed the world's first computerized laboratory information system, speeding analysis and reporting. He directed his team in building computer systems to help clinicians retrieve medical knowledge, enable patients to find information about personal or family health issues, and provide expert automated assistance to physicians in reaching differential diagnoses outside their specialties. Developing superior functionalities with the limited information technologies of the time, Dr. Lindberg's pioneering work in Columbia foreshadowed his subsequent inspired leadership as Director of the United States National Library of Medicine.

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

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.

Assessing the prognoses on Health care in the information society 2013--thirteen years after.

Health care and information technology in health care is advancing at tremendous speed. We analysed whether the prognoses by Haux et al. - first presented in 2000 and published in 2002 - have been fulfilled in 2013 and which might be the reasons for match or mismatch. Twenty international experts in biomedical and health informatics met in May 2013 in a workshop to discuss match or mismatch of each of the 71 prognoses. After this meeting a web-based survey among workshop participants took place. Thirty-three prognoses were assessed matching; they reflect e.g. that there is good progress in storing patient data electronically in health care institutions. Twenty-three prognoses were assessed mismatching; they reflect e.g. that telemedicine and home monitoring as well as electronic exchange of patient data between institutions is not established as widespread as expected. Fifteen prognoses were assessed neither matching nor mismatching. ICT tools have considerably influenced health care in the last decade, but in many cases not as far as it was expected by Haux et al. in 2002. In most cases this is not a matter of the availability of technical solutions but of organizational and ethical issues. We need innovative and modern information system architectures which support multiple use of data for patient care as well as for research and reporting and which are able to integrate data from home monitoring into a patient centered health record. Since innovative technology is available the efficient and wide-spread use in health care has to be enabled by systematic information management.

Past and next 10 years of medical informatics.

More than 10 years ago Haux et al. tried to answer the question how health care provision will look like in the year 2013. A follow-up workshop was held in Braunschweig, Germany, for 2 days in May, 2013, with 20 invited international experts in biomedical and health informatics. Among other things it had the objectives to discuss the suggested goals and measures of 2002 and how priorities on MI research in this context should be set from the viewpoint of today. The goals from 2002 are now as up-to-date as they were then. The experts stated that the three goals: "patient-centred recording and use of medical data for cooperative care"; "process-integrated decision support through current medical knowledge" and "comprehensive use of patient data for research and health care reporting" have not been reached yet and are still relevant. A new goal for ICT in health care should be the support of patient centred personalized (individual) medicine. MI as an academic discipline carries out research concerning tools that support health care professionals in their work. This research should be carried out without the pressure that it should lead to systems that are immediately and directly accepted in practice.

Factors Influencing the Evolution of Topics in Biomedical Informatics.

Our study contributes to the history of international medical informatics through investigating the thematic evolution of the MEDINFO conferences during a period of consolidation and expansion of the discipline. The themes are examined and potential factors influencing the evolutionary developments are discussed.

e-MIR2: a public online inventory of medical informatics resources.

BACKGROUND: Over the past years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for the Medical Informatics (MI) field, so that locating and accessing them currently remains a difficult and time-consuming task. DESCRIPTION: We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. We define informatics resources as all those elements that constitute, serve to define or are used by informatics systems, ranging from architectures or development methodologies to terminologies, vocabularies, databases or tools. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources' names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different classification schemas by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the classification schemas. The classification algorithm identifies the categories associated with resources and annotates them accordingly. The database is then populated with this data after manual curation and validation. CONCLUSIONS: We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contains 609 resources at the time of writing and is available at http://www.gib.fi.upm.es/eMIR2. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers.

Ethics in the History of Medical Informatics for Decision-Making: Early Challenges to Digital Health Goals.

BACKGROUND: Inclusive digital health prioritizes public engagement through digital literacies and internet/web connectivity for advancing and scaling healthcare equitably by informatics technologies. This is badly needed, largely desirable and uncontroversial. However, historically, medical and healthcare practices and their informatics processes assume that individual clinical encounters between practitioners and patients are the indispensable foundation of clinical practice. This assumption has been dramatically challenged by expansion of digital technologies, their interconnectable mobility, virtuality, surveillance informatics, and the vastness of data repositories for individuals and populations that enable and support them. This article is a brief historical commentary emphasizing critical ethical issues about decisions in clinical interactions or encounters raised in the early days of the field. These questions, raised eloquently by François Grémy in 1985, have become urgently relevant to the equity/fairness, inclusivity and unbiasedness desired of today's pervasive digital health systems. OBJECTIVES: The main goal of this article is to highlight how the personal freedoms of choice, values, and responsibilities arising in relationships between physicians and healthcare practitioners and their patients in the clinical encounter can be distorted by digital health technologies which focus more on efficiency, productivity, and scalability of healthcare processes. Understanding the promise and limitations of early and current decision-support systems and the analytics of community or population data can help place into historical context the often exaggerated claims made today about Artificial Intelligence and Machine Learning "solving" clinical problems with algorithms and data, downplaying the role of the clinical judgments and responsibilities inherent in personal clinical encounters. METHODS: A review of selected early articles in medical informatics is related to current literature on the ethical issues and technological inadequacies involved in the design and implementation of clinical systems for decision-making. Early insights and cautions about the development of decision support technologies raised questions about the ethical responsibilities in clinical encounters where freedom of personal choice can be so easily limited through the constraints from information processing and reliance on prior expertise frequently driven more by administrative rather than clinical objectives. These anticipated many of the deeper ethical problems that have arisen since then in clinical informatics. CONCLUSIONS: Early papers on ethics in clinical decision-making provide prescient commentary on the dangers of not taking into account the complexities of individual human decision making in clinical encounters. These include the excessive reliance on data and experts, and oversimplified models of human reasoning, all of which persist and have become amplified today as urgent questions about how inclusivity, equity, and bias are handled in practical systems where ethical responsibilities of individuals patients and practitioners intertwine with those of groups within professional or other communities, and are central to how clinical encounters evolve in our digital health future.

50 Years of Achievements and Persistent Challenges for Biomedical and Health Informatics and John Mantas' Educational and Nursing Informatics Contributions.

Biomedical and Health Informatics (BMHI) have been essential catalysts for achievements in medical research and healthcare applications over the past 50 years. These include increasingly sophisticated information systems and data bases for documentation and processing, standardization of biomedical data, nomenclatures, and vocabularies to assist with large scale literature indexing and text analysis for information retrieval, and methods for computationally modeling and analyzing research and clinical data. Statistical and AI techniques for decision support, instrumentation integration, and workflow aids with improved data/information management tools are critical for scientific discoveries in the - omics revolutions with their related drug and vaccine breakthroughs and their translation to clinical and preventive healthcare. Early work on biomedical image and pattern recognition, knowledge-based expert systems, innovative database, software and simulation techniques, natural language processing and computational ontologies have all been invaluable for basic research and education. However, these methods are still in their infancy and many fundamental open scientific problems abound. Scientifically this is due to persistent limitations in understanding biological processes within complex living environments and ecologies. In clinical practice the modeling of fluid practitioner roles and methods as they adjust to novel cybernetic technologies present great opportunities but also the potential of unintended e-iatrogenic harms which must be constrained in order to adhere to ethical Hippocratic norms of responsible behavior. Balancing the art, science, and technologies of BMHI has been a hallmark of debates about the field's historical evolution. The present article reviews selected milestones, achievements, and challenges in BMHI education mainly, from a historical perspective, including some commentaries from leaders and pioneers in the field, a selection of which have been published online recently by the International Medical Informatics Association (IMIA) as the first volume of an IMIA History WG eBook. The focus of this chapter is primarily on the development of BMHI in terms of those of its educational activities which have been most significant during the first half century of IMIA, and it concentrates mainly on the leadership and contributions of John Mantas who is being honored on his retirement by the Symposia in Athens for which this chapter has been written.

A Scientific Mind Embraces Medicine: Donald Lindberg's Education and Early Career.

As a young pathologist, Donald A.B. Lindberg, M.D., tirelessly sought scientific solutions to clinical and research problems. Directing several clinical laboratories at the University of Missouri in Columbia, Dr. Lindberg developed the world's first computerized laboratory information system, speeding analysis and reporting. He directed his team in building computer systems to help clinicians retrieve medical knowledge, enable patients to find information about personal or family health issues, and provide expert automated assistance to physicians in reaching differential diagnoses outside their specialties. Developing superior functionalities with the limited information technologies of the time, Dr. Lindberg's pioneering work in Columbia foreshadowed his subsequent inspired leadership as Director of the United States National Library of Medicine.

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

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.

Nanoinformatics and DNA-based computing: catalyzing nanomedicine.

Five decades of research and practical application of computers in biomedicine has given rise to the discipline of medical informatics, which has made many advances in genomic and translational medicine possible. Developments in nanotechnology are opening up the prospects for nanomedicine and regenerative medicine where informatics and DNA computing can become the catalysts enabling health care applications at sub-molecular or atomic scales. Although nanomedicine promises a new exciting frontier for clinical practice and biomedical research, issues involving cost-effectiveness studies, clinical trials and toxicity assays, drug delivery methods, and the implementation of new personalized therapies still remain challenging. Nanoinformatics can accelerate the introduction of nano-related research and applications into clinical practice, leading to an area that could be called "translational nanoinformatics." At the same time, DNA and RNA computing presents an entirely novel paradigm for computation. Nanoinformatics and DNA-based computing are together likely to completely change the way we model and process information in biomedicine and impact the emerging field of nanomedicine most strongly. In this article, we review work in nanoinformatics and DNA (and RNA)-based computing, including applications in nanopediatrics. We analyze their scientific foundations, current research and projects, envisioned applications and potential problems that might arise from them.

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

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.

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

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.

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

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.

Roots of Interdisciplinarity in European Medical Informatics.

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.

Ortholog clustering on a multipartite graph.

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.

Personalized case driven parental education informatics in the NICU.

Neonatal Intensive Care Units (NICUs) are foreign and intimidating to parents of premature infants. The high levels of anxiety and stress they can produce needs to be reduced by thoughtful advice from healthcare providers (HCPs), to educate parents about their child's condition. Unfortunately time constraints often limit HCPs to only a few minutes with each baby's parents daily--only enough to convey critical information at a high level and with limited depth. Parents searching for more detailed information themselves in the literature over the web have sometimes reported disappointing experiences. We are proposing to improve parental education by patient-centric web methods leveraging the electronic patient record with internet and cell phone technologies. This can be an important informatics resource, complementing and enhancing face-to-face communication through personalization of education and advice to the parents.

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

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.

Key Relation Extraction from Biomedical Publications.

Within the large body of biomedical knowledge, recent findings and discoveries are most often presented as research articles. Their number has been increasing sharply since the turn of the century, presenting ever-growing challenges for search and discovery of knowledge and information related to specific topics of interest, even with the help of advanced online search tools. This is especially true when the goal of a search is to find or discover key relations between important concepts or topic words. We have developed an innovative method for extracting key relations between concepts from abstracts of articles. The method focuses on relations between keywords or topic words in the articles. Early experiments with the method on PubMed publications have shown promising results in searching and discovering keywords and their relationships that are strongly related to the main topic of an article.