Information Technology in Bio- and Medical Informatics, ITBAM 2010

ACM SIGHIT Record, 2012

Advances of high throughput technologies have yielded the possibility to investigate human cells of healthy and morbid ones at different levels. Consequently, this has made possible the discovery of new biological and biomedical data and the proliferation of a large number of databases. In this paper, we describe the IS-BioBank (Integrated Semantic Biological Data Bank) proposal. It consists of the realization of a framework for enabling the interoperability among different biological data sources and for ultimately supporting expert users in the complex process of extraction, navigation and visualization of the precious knowledge hidden in such a huge quantity of data. In this framework, a key role has been played by the Connectivity Map, a databank which relates diseases, physiological processes, and the action of drugs. The system will be used in a pilot study on the Multiple Myeloma (MM).

Availability of timely and accurate data is vital to make informed medical decisions. Every type of health care organisation faces a common problem with the considerable amount of data they have in several systems. Such systems are unstructured and unorganised, demanding computational time for data and information integration. Data required to make informed medical decisions are trapped within fragmented and disparate clinical and administrative systems that are not properly integrated or fully utilised. The process of synthesising information from these multiple heterogeneous data sources is extremely difficult and time consuming. Ultimately, health care begins to constrain because, medical practitioners and health care providers are unable to access and use this information to improve patient care.

2009

The expansion of biomedical knowledge, reductions in computing costs and spread of IT facilities have led to an explosion of the biomedical electronic data. However, these data are rarely integrated and analysed because of lack of tools. The integration process is complex due to technical and semantic heterogeneity as well as lack of reliability in such distributed system. In addition, for the specific case of biomedical data, privacy is a crucial constraint. This paper presents a pilot system that will be used in the European FP7 DebugIT project to integrate biomedical data from several healthcare centres across Europe.

Swiss-German University, Bumi Serpong Damai 2012

Medical Information Systems is standardized methods of collection, evaluation or verification, storage, and retrieval of data about a patient. This science is a combination of several fields of study such as information and communication technology, information systems, management, and medical. The course provides an overview of the field of health informatics, covering the main challenges to modern healthcare which are driving its development, research trends and emerging technologies. A particular focus will be to understand the role that informatics plays in addressing the difficult problem of implementing IS and IT into clinical practice.

... Formal Methods. Proceedings of the First International Conference on Software Engineering and Formal Methods (2003) . Edited by Antonio Cerone and Peter Lindsay. ... Methods. Editor(s), Antonio Cerone Peter Lindsay. Conference ...

ABSTRACT As organizations grow larger and more distributed, the problems of maintaining corporate awareness and effective communication channels escalate. The clinical domain poses particular challenges to maintaining good corporate communications because users have limited time to access information and often have negative technology perceptions.

Lecture Notes in Computer Science, 2000

Yearbook of medical informatics, 2007

Objectives: To summarize and highlight the role of IMIA in the past 40 years in becoming the international professional organization that brings together researchers, practitioners, and educators in the field of medical informatics, and more broadly biomedical, nursing, and health informatics Method: Outlining developments of medical informatics related to IMIA from 1967 to 2007 in a time-line and comparative topic and geographical distribution analyses over selected MEDINFOs from 1980 and selected Yearbooks from 1992 onwards. This illustrates how IMIA, through the global reach of its activities, has helped advance the science and development of informatics across the entire spectrum of biomedical and health care research, education, and practice. Results and conclusions: The contribution of IMIA over the past 40 years has been to sponsor and coordinate international conferences and promote interchange and collaborations in biomedical and health informatics by linking national and regional societies, organizing meetings, high quality publications, and working groups. These have helped the coalescing of the discipline worldwide, promoting full participation and a broad interdisciplinary scope that fulfills the hopes of the pioneers in the field.

Proceedings of Spie the International Society For Optical Engineering, 2009

The current trend towards systems medicine will rely heavily on computational and bioinformatics capabilities to collect, integrate, and analyze massive amounts of data from disparate sources. The objective is to use this information to make medical decisions that improve patient care. At Georgetown University Medical Center, we are developing an informatics capability to integrate several research and clinical databases. Our long term goal is to provide researchers at Georgetown's Lombardi Comprehensive Cancer Center better access to aggregated molecular and clinical information facilitating the investigation of new hypotheses that impact patient care. We also recognize the need for data mining tools and intelligent agents to help researchers in these efforts. This paper describes our initial work to create a flexible platform for researchers and physicians that provides access to information sources including clinical records, medical images, genomic, epigenomic, proteomic and metabolomic data. This paper describes the data sources selected for this pilot project and possible approaches to integrating these databases. We present the different database integration models that we considered. We conclude by outlining the proposed Information Model for the project.

Biomedical Informatics

Contents 30.1 The Present and Its Evolution from the Past-988 30.2 Looking to the Future-994 References-1016. Table 30.1 Table of contents sections and chapters from all five editions of this book, aligned by subject matter Medical Informatics: Computer Applications in Medical Care (1990) Medical Informatics: Computer Applications in Health Care and Biomedicine (2000) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2006) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2014) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2020) Recurrent themes in medical informatics Recurrent themes in medical informatics Recurrent themes in biomedical informatics Recurrent themes in biomedical informatics Recurrent themes in biomedical informatics 1. The computer meets medicine: Emergence of a discipline 30 (continued). Table 30.1 (continued) Medical Informatics: Computer Applications in Medical Care (1990) Medical Informatics: Computer Applications in Health Care and Biomedicine (2000) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2006) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2014) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2020) 4. Cognitive science and biomedical informatics 10. Imaging and structural informatics 9. Bioinformatics 11. Personal health informatics 7. Ethics and health informatics: Users, standards, and outcomes 10. Ethics and health informatics: Users, standards, and outcomes 10. Ethics in biomedical and health informatics: Users, standards, and outcomes 12. Ethics in biomedical and health informatics: Users, standards, and outcomes 8. Evaluation and technology assessment 11. Evaluation and technology assessment 11. Evaluation of biomedical and health information resources 13. Evaluation of biomedical and health information resources The Future of Informatics in Biomedicine 990 30. Table 30.1 (continued) Medical Informatics: Computer Applications in Medical Care (1990) Medical Informatics: Computer Applications in Health Care and Biomedicine (2000) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2006) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2014) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2020) Medical computing applications Medical computing applications Biomedical informatics applications Biomedical informatics applications Biomedical informatics applications 6. Medical-record systems 9. Computer-based patient record systems 12. Electronic health record systems 30. Table 30.1 (continued) Medical Informatics: Computer Applications in Medical Care (1990) Medical Informatics: Computer Applications in Health Care and Biomedicine (2000) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2006) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2014) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (2020) Basic Science

Journal of Medical Systems

Medical Informatics (or health informatics) is considered the science of applying the methods of computer science to health-care. In particular, medical informatics provides methodologies for systematic organization, representation, and analytics of data that is collected in health and well-being. About 50 years ago, the goal has been worded by Peter L. Reichertz: "the right information at the right place at the right time". In this regard, the European Federation for Medical Informatics (EFMI), which is composed of national member societies, such as the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), organizes annually a special topic conference (STC) that specialize in current trends in medical informatics. The 2019 edition of EFMI STC was focused on information and communication technology (ICT) for Health Science Research. A major challenge in this field is the syntactical and semantical integration of ICT systems, since much of the data for health science research is coming from healthcare. Nevertheless, research often requires data of higher resolution, precision, and quality than is typically available in healthcare ICT systems. Thus, healthcare data are extracted, transformed, and loaded into research data warehouses, which leads to duplication of data and might challenge data integrity from specific individuals across research and healthcare systems, possibly hindering personalized medicine and translational research. ICT systems for health science research are used in application domains such as clinical trials, development of drugs and medical devices, as well as translational medicine, aiming at better prevention, diagnostics, and interventions in health and care. In addition, ethical, legal, and social aspects of health data are considered. EFMI STC 2019 was held at the Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School in Hanover, Germany. It was jointly organized with the celebration of the 50th anniversary of the appointment of Peter L. Reichertz to the Hannover Medical School, which founded medical informatics as a research field in Germany in 1969. From the total of 87 paper submissions, the scientific program committee (SPC)-which was strictly different from the local organizing committee (LOC)-selected 48 oral and 22 poster presentations, which have been published in the conference proceedings [1]. However, the authors could decide to publish only an abstract within the proceedings and submit the extended paper to this special topic at JOMS. Seven of these submissions finally have passed the strict peer-review process, which, due to the Conora pandemic, lasts almost two years. These papers focus on research and development of information systems supporting biomedical, translational, and clinical research, as well as interoperability across such systems for the purpose of data integration, improving findability, and supporting analytics of cross-system data. They all have been submitted before the pandemic, but have been published during the pandemic. Therefore, we partly reflect them in the light of COVID-19, too.

Journal of Medical Systems, 2014

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 This article is part of the Topical Collection on Special Issue: Health Care in the Information Society-a Prognosis for the Year 2013

As the use of Electronic Medical Records (EMRs) becomes more widespread, so does the need to look and give viable information disclosure on them. Information disclosure strategies will permit experts and other healthcare stakeholders to find significant pieces of information in the growing corpus of accessible EMRs. The victory of Web look motors has appeared that keyword questions are a valuable device for locating significant information in an instinctive and viable manner. However, questions emerge of the form: What are the semantics of keyword questions on EMRs? What is a vital result? What is the role of medical and clinical ontologies and Lexicons like SNOMED (Systematized Classification of Human and Veterinary Medicine) in answering such queries? In this position paper we introduce the issue of keyword-based information disclosure on EMRs and enumerate the salient challenges that must be addressed to encourage quality information discovery. The objective is to make interest in new medical information administration relook initiatives, and conceivably make new paradigms for utilizing medical data. The primary center of the paper is the newest XML-based EMR standard created by the Health Level Seven (HL7) group, the Clinical Archive Engineering (CDA) Release 2.0, although the same issues emerge for any other standard hierarchical format.

European Radiology Experimental

PRIMAGE is a European Commission-financed project dealing with medical imaging and artificial intelligence aiming to create an imaging biobank in oncology. The project includes a task dedicated to the interoperability between imaging and standard biobanks. We aim at linking Digital imaging and Communications in Medicine (DICOM) metadata to the Minimum Information About BIobank data Sharing (MIABIS) standard of biobanking. A very first integration model based on the fusion of the two existing standards, MIABIS and DICOM, has been developed. The fundamental method was that of expanding the MIABIS core to the imaging field, adding DICOM metadata derived from CT scans of 18 paediatric patients with neuroblastoma. The model was developed with the relational database management system Structured Query Language. The integration data model has been built as an Entity Relationship Diagram, commonly used to organise data within databases. Five additional entities have been linked to the “Imag...

2015