Showing papers on "Translational research informatics published in 2015"

OncDRS: An integrative clinical and genomic data platform for enabling translational research and precision medicine

Abstract: We live in the genomic era of medicine, where a patient's genomic/molecular data is becoming increasingly important for disease diagnosis, identification of targeted therapy, and risk assessment for adverse reactions. However, decoding the genomic test results and integrating it with clinical data for retrospective studies and cohort identification for prospective clinical trials is still a challenging task. In order to overcome these barriers, we developed an overarching enterprise informatics framework for translational research and personalized medicine called Synergistic Patient and Research Knowledge Systems (SPARKS) and a suite of tools called Oncology Data Retrieval Systems (OncDRS). OncDRS enables seamless data integration, secure and self-navigated query and extraction of clinical and genomic data from heterogeneous sources. Within a year of release, the system has facilitated more than 1500 research queries and has delivered data for more than 50 research studies.

Defining Informatics across Bun-kei and Ri-kei

Abstract: The Science Council of Japan’s Committee on Informatics is currently creating a reference standard in informatics. This activity includes defining informatics for university education and for the future academic development of informatics. The most characteristic feature of the chosen definition of informatics is the desire to cover all branches of informatics across bun-kei (social sciences and humanities) and ri-kei (natural science and engineering), with the intention of unifying the field. In the present paper, the background of the activity, and the motivation and implications of the definition of informatics are presented. In particular, we discuss the importance of covering bun-kei and ri-kei for the future development of informatics and the implications of the definition on liberal arts education in universities and primary and secondary education in elementary, middle and high schools.

Interdisciplinary training to build an informatics workforce for precision medicine.

Abstract: The proposed Precision Medicine Initiative has the potential to transform medical care in the future through a shift from interventions based on evidence from population studies and empiric response to ones that account for a range of individual factors that more reliably predict response and outcomes for the patient. Many things are needed to realize this vision, but one of the most critical is an informatics workforce that has broad interdisciplinary training in basic science, applied research and clinical implementation. Current approaches to informatics training do not support this requirement. We present a collaborative model of training that has the potential to produce a workforce prepared for the challenges of implementing precision medicine.

Emerging medical informatics research trends detection based on MeSH terms.

Abstract: The aim of this study is to analyze the research trends of medical informatics over the last 12 years. A new method based on MeSH terms was proposed to identify emerging topics and trends of medical informatics research. Informetric methods and visualization technologies were applied to investigate research trends of medical informatics. The metric of perspective factor (PF) embedding MeSH terms was appropriately employed to assess the perspective quality for journals. The emerging MeSH terms have changed dramatically over the last 12 years, identifying two stages of medical informatics: the ‘‘medical imaging stage’’ and the ‘‘medical informatics stage’’. The focus of medical informatics has shifted from acquisition and storage of healthcare data by integrating computational, informational, cognitive and organizational sciences to semantic analysis for problem solving and clinical decision-making. About 30 core journals were determined by Bradford’s Law in the last 3 years in this area. These journals, with high PF values, have relative high perspective quality and lead the trend of medical informatics.

Big data issues in medical imaging informatics

Abstract: The issues of big data in medical imaging informatics have special characters which need to be deal with in healthcare service and research. These characters lead to many technical challenges in medical imaging informatics. The data set sizes and hiding states of medical imaging are major factors which make big data of medical imaging be quite different from other kind of big data. The possible and perspective solutions of big data issues in medical imaging informatics are discussed in this presentation, and also some of our research projects related to five V features of big data in medical imaging and informatics have been briefed.

Next generation informatics for big data in precision medicine era.

Abstract: The rise of data-intensive biology, advances in informatics technology, and changes in the way health care is delivered has created an compelling opportunity to allow us investigate biomedical questions in the context of “big data” and develop knowledge systems to support precision medicine. To promote such data mining and informatics technology development in precision medicine, we hosted two international informatics workshops in 2014: 1) the first workshop on Data Mining in Biomedical informatics and Healthcare, in conjunction with the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014), and 2) the first workshop on Translational biomedical and clinical informatics, in conjunction with the 8th International Conference on Systems Biology and the 4th Translational Bioinformatics Conference (ISB/TBC 2014). This thematic issue of BioData Mining presents a series of selected papers from these two international workshops, aiming to address the data mining needs in the informatics field due to the deluge of “big data” generated by next generation biotechnologies such as next generation sequencing, metabolomics, and proteomics, as well as the structured and unstructured biomedical and healthcare data from electronic health records. We are grateful for the BioData Mining’s willingness to produce this forward-looking thematic issue.

Bioinformatics Methods and Tools to Advance Clinical Care

Abstract: Objectives: To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain and clinical care. Method: We provide a synopsis of the articles selected for the IMIA Yearbook 2015, from which we attempt to derive a synthetic overview of current and future activities in the field. As last year, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor has evaluated separately the set of 1,594 articles and the evaluation results were merged for retaining 15 articles for peer-review. Results: The selection and evaluation process of this Yearbook's section on Bioinformatics and Translational Informatics yielded four excellent articles regarding data management and genome medicine that are mainly tool-based papers. In the first article, the authors present PPISURV a tool for uncovering the role of specific genes in cancer survival outcome. The second article describes the classifier PredictSNP which combines six performing tools for predicting disease-related mutations. In the third article, by presenting a high-coverage map of the human proteome using high resolution mass spectrometry, the authors highlight the need for using mass spectrometry to complement genome annotation. The fourth article is also related to patient survival and decision support. The authors present datamining methods of large-scale datasets of past transplants. The objective is to identify chances of survival. Conclusions: The current research activities still attest the continuous convergence of Bioinformatics and Medical Informatics, with a focus this year on dedicated tools and methods to advance clinical care. Indeed, there is a need for powerful tools for managing and interpreting complex, large-scale genomic and biological datasets, but also a need for user-friendly tools developed for the clinicians in their daily practice. All the recent research and development efforts contribute to the challenge of impacting clinically the obtained results towards a personalized medicine.

*informatics: Identifying and Tracking Informatics Sub-Discipline Terms in the Literature.

Abstract: Objective: To identify the breadth of informatics sub-discipline terms used in the literature for enabling subsequent organization and searching by sub-discipline. Methods: Titles in five literature sources were analyzed to extract terms for informatics sub-disciplines: 1) United States (U.S.) Library of Congress Online Catalog, 2) English Wikipedia, 3) U.S. National Library of Medicine (NLM) Catalog, 4) PubMed, and 5) PubMed Central. The extracted terms were combined and standardized with those in four vocabulary sources to create an integrated list: 1) Library of Congress Subject Headings (LCSH), 2) Medical Subject Headings (MeSH), 3) U.S. National Cancer Institute Thesaurus (NCIt), and 4) EMBRACE Data and Methods (EDAM). Searches for terms in titles from each literature source were conducted to obtain frequency counts and start years for characterizing established and potentially emerging sub-disciplines. Results: Analysis of 6,949 titles from literature sources and 67 terms from vocabulary sources resulted in an integrated list of 382 terms for informatics sub-disciplines mapped to 292 preferred terms. In the last five decades, “bioinformatics”, “medical informatics”, “health informatics”, “nursing informatics”, and “biomedical informatics” were associated with the most literature. In the current decade, potentially emerging sub-disciplines include “disability informatics”, “neonatal informatics”, and “nanoinformatics” based on literature from the last five years. Conclusions: As the field of informatics continues to expand and advance, keeping up-to-date with historical and current trends will become increasingly challenging. The ability to track the accomplishments and evolution of a particular sub-discipline in the literature could be valuable for supporting informatics research, education, and training.

Medical Informatics: Past and Future

Abstract: Led in its earliest decades by a few pioneers and supported by a small number of professional organizations and universities, medical informatics was funded primarily by federal grants and contracts until 1980, when industry began to enter the marketplace. Despite technology advances, diffusion across health care was slow, and computers were used predominately for business functions. In the 1980s specialized subsystems were developed for the clinical laboratory, radiology, and pharmacy, but by 1989 only a few medical information systems were operational, most of them in academic health centers that had received federal funding. In the 1990s, distributed information systems allowed physicians to enter orders and retrieve test results using clinical workstations; and hospital networks integrated data from all the distributed clinical specialty databases in an electronic patient record. By the end of 1990s, systems were up and running in the Department of Defense and Veterans Administration. In the 2000s, more clinicians in the United States were using electronic health records, due in part to steps taken to adjust the computer to its professional users. Diffusion was further advanced in 2010, when direct federal funding was extended to health care providers using systems that met “Meaningful Use” requirements in caring for Medicare and Medicaid patients. Advances expected in the next decade include precision medicine and patient genotyping; telehealth care; cloud computing; support for elder care with multiple chronic diseases and polypharmacy; advanced clinical decision support; patient data security; big data analytics, improved population health, public health, and disaster management; and interoperability and integration of care across venues.

Biomedical Big Data Analytics for Patient-Centric and Outcome-Driven Precision Health

Abstract: Rapid advancements in biotechnologies such as -omic (genomics, proteomics, metabolomics, lipidomics etc), next generation sequencing, bio-nanotechnologies, molecular imaging, and mobile sensors etc accelerate the data explosion in biomedicine and health wellness Multiple nations around the world have been seeking novel effective ways to make sense of "big data" for evidence-based, outcome-driven, and affordable 5P (Patient-centric, Predictive, Preventive, Personalized, and Precise) healthcare My main research focus is on multi-modal and multi-scale (ie molecular, cellular, whole body, individual, and population) biomedical data analytics for discovery, development, and delivery, including translational bioinformatics in biomarker discovery for personalized care; imaging informatics in histopathology for clinical diagnosis decision support; bionanoinformatics for minimally-invasive image-guided surgery; critical care informatics in ICU for real-time evidence-based decision making; and chronic care informatics for patient-centric health In this talk, first, I will highlight major challenges in biomedical and health informatics pipeline consisting of data quality control, information feature extraction, advanced knowledge modeling, decision making, and proper action taking through feedback Second, I will present informatics methodological research in (i) data integrity and integration; (ii) case-based reasoning for individualized care; and (iii) streaming data analytics for real-time decision support using a few mobile health case studies (eg Sickle Cell Disease, asthma, pain management, rehabilitation, diabetes etc) Last, there is big shortage of data scientists and engineers who are capable of handling Big Data In addition, there is an urgent need to educate healthcare stakeholders (ie patients, physicians, payers, and hospitals) on how to tackle these grant challenges I will discuss efforts such as patient-centric educational intervention, community-based crowd sourcing, and Biomedical Data Analytics MOOC development Our research has been supported by NIH, NSF, Georgia Research Alliance, Georgia Cancer Coalition, Emory-Georgia Tech Cancer Nanotechnology Center, Children's Health Care of Atlanta, Atlanta Clinical and Translational Science Institute, and industrial partners such as Microsoft Research and HP

Data Analytics in Healthcare Informatics

Abstract: In recent years, the introduction of data analytics to large amounts of healthcare data collected on daily basis opened numerous new opportunities and challenges in the field of medical informatics. By definition, healthcare informatics refers to the process of leveraging information technologies to improve the quality of healthcare. Many researchers are focusing on basic and translational research to achieve this goal by proposing novel or applying and adapting the state-of-the-art data analytics techniques to vast amounts of recently collected data. Recent adoption of Electronic Health Records (EHR) opens additional opportunities for data analytics, as we are able to access structured and unstructured data that is systematically collected for each event in the healthcare system or even contributed by the patients themselves. This tutorial covers different data analytics techniques and their translational value in improving the quality of healthcare. In the introductory part of the tutorial, we will outline the basics of data analytics in healthcare and continue with description of data representation that is specific to this field. The second part of the tutorial will present concrete state-of-the-art approaches that can be applied in healthcare informatics. Participants will gain a better understanding of risk estimation and stratification, patient similarity, privacy-preserving predictive modelling and patient-based classification. All methods presented in the tutorial have great translational value and can be implemented as a stand-alone solution or a part of health information systems. The intended audience of this tutorial are healthcare professionals and researchers from all fields of healthcare informatics. No specific knowledge will be required since the tutorial is self-contained and most fundamental concepts will be introduced during the presentation.

Guest-EditorialBiomedical Informatics in Clinical Environments

Abstract: The aim of this special section is to provide an overview of the emerging biomedical informatics technologies and their application in research and clinical environments. Recent developments in biomedical informatics have created methods, techniques and tools, which are based on the analysis of heterogeneous data, data mining, decision support systems, multiscale modeling, etc. The distance from the development of such systems and the real clinical environments is still long enough, and only some of them have been used in a clinical scale.

Clinical and Translational Research: Expanding Opportunities!

Abstract: CCTR 520. Fundamentals of Research Regulation. 2 Hours. Semester course; 2 lecture hours. 2 credits. Focuses on the regulations that govern translational and clinical research. There will also be a series of discussions on the influence of international policies and research guidelines on the conduct of research. Topics include, but are not limited to, the history and current role of the FDA and the OHRP within the research arena; informed consent regulations relevant to federally funded research i.e., the common rule; informed consent regulations relevant to investigations conducted in support of a new drug application or an expanded marketing indication; good clinical practice guidelines; international conference on harmonization (ICH) conduction of research guidelines; HIPPA rules and regulations relevant to the conduction of research on human subjects; fiscal accountability/responsibility; and clinical trial registration and results reporting guidelines.

Research in nursing informatics 2014.

Abstract: This article reflects the work done in the third year of the Nursing Informatics Year in Review project. This project seeks to search and analyze articles written by nurses as first author on the subject of nursing informatics, published August 2013-August 2014. Each year we also seek recommended articles from our American Medical Informatics Association-Nursing Informatics Work Group (AMIA-NIWG) members that meet the same criteria as the search and most influenced their thinking and scholarship. Twenty-seven articles emerged from the literature review, and our AMIA-NIWG members recommended 32 articles. We analyzed the articles by journal of publication, country of first author, source of funding, research method, research setting, and area of focus. The purpose of this article was to present the results of this project for 2014.

An Introduction to Translational Informatics and the Future of Knowledge-Driven Healthcare

Abstract: Emergent and multidisciplinary research paradigms have fundamentally transformed biomedical science and the delivery of clinical care. This shift has been manifested in a number of ways, including the rapid growth and increasing availability of high-throughput bio-molecular instrumentation and analysis platforms, innovative clinical research programs intended to accelerate the exchange of knowledge between various stakeholders, efforts to deliver precision or personalized healthcare informed by the unique molecular phenotypes of patients, and a growing focus on patient-centered research that occurs at the point-of-care and beyond. A common theme spanning such transformative changes is the use of rigorous and systematic approaches to the collection, management, integration, analysis, and dissemination of large-scale and heterogeneous data sets. Unfortunately, the absence of well-established theoretical and practical frameworks intended to address such needs remains a major impediment to the realization of a translational and knowledge-driven healthcare system, in which the best possible scientific evidence is used to inform the care of every patient. In this vacuum, the development of integrative clinical or translational research paradigms is significantly limited by the propagation of both data and expertise silos. In this and subsequent chapters of this book, we will present a broad framework and specific examples of how the deep integration of biomedical informatics with both biomedical research and clinical care delivery is essential to overcoming such barriers and achieving the benefits of a knowledge-based approach to the delivery of high-performance, quality, safe, and individually tailored healthcare.

A Multi-disciplinary Science of Human Computer Interaction in Biomedical Informatics

Abstract: Health information technologies have become vital tools for the practice of clinical medicine. However, numerous challenges remain for the fuller realization of its potential as instruments that advance clinical care and enhance patient safety. Human-computer interaction (HCI) is a discipline rooted in computer science as well as the social and behavioral sciences. It is focally concerned with evaluating and improving user experience, usability, and usefulness of technology. HCI in medicine and healthcare, the subject matter of this volume, extends across clinical and consumer health informatics, addressing a range of user populations including providers, biomedical scientists and patients. The breadth of HCI in biomedicine and healthcare is rather broad including thousands of journal articles across medical disciplines and consumer health domains. Although the 14 chapters in this volume are rather varied in subject matter and scope, there is greater focus on clinical informatics with a couple of chapters addressing consumer health informatics issues. This introductory chapter provides a brief overview of the other chapters in this volume.

Medical Informatics Specialty in the Developed English-Speaking Countries: The Terminology Comparative Analysis.

Abstract: Abstract The article studies the development process of medical informatics specialty terminology as the ground for further research into foreign countries’ experience, including the Canadian one, of specialists’ professional training in the field of MI. The study determines the origin and chief stages of the formation and development of the medical informatics terminological system. The author performs the comparative analysis of terms used by the world organizations on health care informatisation issues, particularly International Medical Informatics Association as well as medical informatics associations of the USA and Canada as the leading countries where qualified workforce in the medical informatics specialty is trained. The European and Ukrainian experience has also been taken into consideration. The results of the comparative study have shown that the English terms ‘medical informatics’, ‘biomedical informatics’ and ‘health informatics’ serve as the umbrella terms for professional training programs and include a set of subspecialties that identify diverse spheres of information technology applications to medical science and practice, namely ‘clinical informatics’, ‘bioinformatics’, ‘health care informatics’, ‘nursing informatics’, ‘imaging informatics’, etc.

Driving Clinical and Translational Research Using Biomedical Informatics

Abstract: The conduct of clinical and translational research projects is complex and often computationally intensive due to multiple types of co-occurring information needs. At every step, from project conceptualization to design to implementation, a variety of data and knowledge resources are either consumed or produced. As such, the conduct of clinical and translational research requires the availability of comprehensive and systematic data, information, and knowledge management tools and methods. The importance of such platforms and techniques is greatly amplified when projects involve geographically or temporally distributed teams, as well as when their scientific aims correspond with the need to collect, manage, and analyze multi-dimensional or heterogeneous data sets (for example, when a study involves the collection and integrative analysis of patient-derived clinical and bio-molecular phenotypes). In this chapter, we will review the basic types of studies that may be conducted in a clinical or translational research context, and the information needs associated with such paradigms. We will then introduce the broad classes of informatics theories and methods capable of addressing such requirements. Finally, we will discuss the way in which such study designs and enabling or predisposing informatics mechanisms can be contextualized in the “real world”, spanning a spectrum from the lab to the laptop to the living room.

Establishment of research-oriented hospital: an important way for translational medicine development in China.

Abstract: Globally, one of the major trends is the development of translational medicine. The traditional hospital structure could not meet the demands of translational medicine development any longer and to explore a novel hospital structure is imperative. Following the times, China proposed and implemented a development strategy for a first-class modern research-oriented hospital. To establish a research-oriented hospital has become an important strategy to guide the scientific development of high-quality medical institutions and to advance translational medicine development. To facilitate translational medicine by developing research-oriented hospital, the Chinese Research Hospital Association (CRHA) has been established, which provides service of medicine, talents cultivation, scientific research and clinical teaching and covers areas of theoretical research, academic exchange, translational medicine, talents training and practice guiding. On the whole, research-oriented hospital facilitated translational medicine by developing interdisciplinary platform, training core competencies in clinical and translational research, providing financial support of translational research, and hosting journals on translational medicine, etc.

Health Informatics - Introduction

Abstract: 1. Hassan A. Aziz, PhD, MLS(ASCP)cm[⇑][1] 1. College of Arts and Sciences, Qatar University, Doha – Qatar 1. Address for Correspondence: Hassan A. Aziz, PhD, MLS(ASCP)cm, Associate Dean for Academic Affairs, Director and Associate Professor of Biomedical Science, College of Arts and Sciences, Qatar University, P.O. Box: 2713, Doha – Qatar, 00974-4403-4783, Hassan.Aziz{at}qu.edu.qa INTRODUCTION Health informatics is a wide-ranging science incorporating the complex mixture of people, organizations, illnesses, patient care and treatment. It is a scientific field that deals with the storage, retrieval, sharing, and optimal use of biomedical information, data, and knowledge for problem solving and decision making. The field touches on all basic and applied fields in biomedical science and is closely tied to modern information technologies, notably in the areas of computing and communication. Health informatics looks into ways to optimize clinical knowledge creation, sharing and application to deliver better healthcare and to promote health. The emergence of medical informatics as a new discipline is due in large part to the rapid advances in computing and communications technologies, an increasing awareness that the knowledge base of biomedicine is essentially unmanageable by traditional paper-based methods, and a growing conviction that the process of informed decision making is as important to modern biomedicine as is the collection of facts on which clinical decisions or research plans are made. A term is currently used is Big Data. The term describes large and exponential growth and availability of data. These data could be structured or unstructured data. This is well defined as data that adhere to the following four articulated criteria. The first criteria is volume, which is considered to be an ever-increasing amount. With the emergence of various storage devices and the reduction of the storage cost it is made increasingly possible to manage this large volume of data. However, strict evaluation of… [1]: #corresp-1

Future Directions for Translational Informatics

Abstract: In order to realize the great promise of knowledge-driven healthcare, we must capitalize upon the advances in translational informatics made to date. While some of the necessary technological infrastructure is now in place or actively being implemented, and while the drive to leverage that infrastructure is strong in many sectors of society, there remain many challenges to realizing the vision of translational informatics and thereby substantial improvements in healthcare and biomedicine. In addition to improving the design and optimizing the use of health information technologies, myriad organizational, cultural and regulatory changes are needed to fully realize this vision. Only by so doing, will we as a society finally be able to create and leverage information ecosystems that are efficient and effective at simultaneously advancing not only the practice of evidence-based medicine, but the systematic generation of evidence at every point in the healthcare and biomedical research lifecycle. Indeed, such changes are essential to creating a true “learning health system” that drives not only more effective care while accelerating scientific advances, but does so in a manner that is both affordable today and sustainable for the benefit of the entire population well into the future.

Information Technology for Clinical, Translational and Comparative Effectiveness Research. Findings from the Yearbook 2015 Section on Clinical Research Informatics.

Abstract: Objectives To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain and clinical care. Method We provide a synopsis of the articles selected for the IMIA Yearbook 2015, from which we attempt to derive a synthetic overview of current and future activities in the field. As last year, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor has evaluated separately the set of 1,594 articles and the evaluation results were merged for retaining 15 articles for peer-review. Results The selection and evaluation process of this Yearbook's section on Bioinformatics and Translational Informatics yielded four excellent articles regarding data management and genome medicine that are mainly tool-based papers. In the first article, the authors present PPISURV a tool for uncovering the role of specific genes in cancer survival outcome. The second article describes the classifier PredictSNP which combines six performing tools for predicting disease-related mutations. In the third article, by presenting a high-coverage map of the human proteome using high resolution mass spectrometry, the authors highlight the need for using mass spectrometry to complement genome annotation. The fourth article is also related to patient survival and decision support. The authors present datamining methods of large-scale datasets of past transplants. The objective is to identify chances of survival. Conclusions The current research activities still attest the continuous convergence of Bioinformatics and Medical Informatics, with a focus this year on dedicated tools and methods to advance clinical care. Indeed, there is a need for powerful tools for managing and interpreting complex, large-scale genomic and biological datasets, but also a need for user-friendly tools developed for the clinicians in their daily practice. All the recent research and development efforts contribute to the challenge of impacting clinically the obtained results towards a personalized medicine.