Developing Predictive Molecular Maps of Human Disease through Community-based Modeling

The failure of biology to identify the molecular causes of disease has led to disappointment in the rate of development of new medicines. By combining the power of community-based modeling with broad access to large datasets on a platform that promotes reproducible analyses we can work towards more predictive molecular maps that can deliver better therapeutics

Cross‐campus Collaboration: A Scientometric and Network Case Study of Publication Activity Across Two Campuses of a Single Institution

Team science and collaboration have become crucial to addressing key research questions confronting society. Institutions that are spread across multiple geographic locations face additional challenges. To better understand the nature of cross‐campus collaboration within a single institution and the effects of institutional efforts to spark collaboration, we conducted a case study of collaboration at Cornell University using scientometric and network analyses. Results suggest that cross‐campus collaboration is increasingly common, but is accounted for primarily by a relatively small number of departments and individual researchers. Specific researchers involved in many collaborative projects are identified, and their unique characteristics are described. Institutional efforts, such as seed grants and topical retreats, have some effect for researchers who are central in the collaboration network, but were less clearly effective for others

The effect of multidisciplinary collaborations on research diversification

This work verifies whether research diversification by a scientist is in some measure related to their collaboration with multidisciplinary teams. The analysis considers the publications achieved by 5300 Italian academics in the sciences over the period 2004-2008. The findings show that a scientist's outputs resulting from research diversification are more often than not the result of collaborations with multidisciplinary teams. The effect becomes more pronounced with larger and particularly with more diversified teams. This phenomenon is observed both at the overall level and for the disciplinary macro-areas

The quality of reports of medical and public health research from Palestinian institutions:A systematic review

Research reports are the most common way to communicate research findings for target readerships. Complete, accurate and transparent reporting of research studies facilitates dissemination, interpretation, translation and replication of research findings. Inadequate reporting has major consequences for clinicians, researchers, policy makers and ultimately patients. It impairs critical assessment of the validity, relevance and trustworthiness of research and so impedes its use in practice. It also limits the usability of study findings by other researchers conducting systematic reviews and meta-analyses and building on or replicating studies. In addition, inadequate reporting is one of the key contributors to avoidable waste in biomedical research. Researchers thus have an ethical obligation to research participants, funding organisations and society as a whole to report their findings in ways that are of use in practice and policy makin

Biomedical Research, A Tool to Address the Health Issues that Affect African Populations.

Traditionally, biomedical research endeavors in low to middle resources countries have focused on communicable diseases. However, data collected over the past 20 years by the World Health Organization (WHO) show a significant increase in the number of people suffering from non-communicable diseases (e.g. heart disease, diabetes, cancer and pulmonary diseases). Within the coming years, WHO predicts significant decreases in communicable diseases while non-communicable diseases are expected to double in low and middle income countries in sub-Saharan Africa. The predicted increase in the non-communicable diseases population could be economically burdensome for the basic healthcare infrastructure of countries that lack resources to address this emerging disease burden. Biomedical research could stimulate development of healthcare and biomedical infrastructure. If this development is sustainable, it provides an opportunity to alleviate the burden of both communicable and non-communicable diseases through diagnosis, prevention and treatment. In this paper, we discuss how research using biomedical technology, especially genomics, has produced data that enhances the understanding and treatment of both communicable and non-communicable diseases in sub-Saharan Africa. We further discuss how scientific development can provide opportunities to pursue research areas responsive to the African populations. We limit our discussion to biomedical research in the areas of genomics due to its substantial impact on the scientific community in recent years however, we also recognize that targeted investments in other scientific disciplines could also foster further development in African countries

Understanding safety-critical interactions with a home medical device through Distributed Cognition

As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has been a useful theoretical framework for understanding situated interactions in the healthcare domain. However, it has not previously been applied to study interactions with home medical devices. In this study, DCog was applied to understand renal patients’ interactions with Home Hemodialysis Technology (HHT), as an example of a home medical device. Data was gathered through ethnographic observations and interviews with 19 renal patients and interviews with seven professionals. Data was analyzed through the principles summarized in the Distributed Cognition for Teamwork methodology. In this paper we focus on the analysis of system activities, information flows, social structures, physical layouts, and artefacts. By explicitly considering different ways in which cognitive processes are distributed, the DCog approach helped to understand patients’ interaction strategies, and pointed to design opportunities that could improve patients’ experiences of using HHT. The findings highlight the need to design HHT taking into consideration likely scenarios of use in the home and of the broader home context. A setting such as home hemodialysis has the characteristics of a complex and safety-critical socio-technical system, and a DCog approach effectively helps to understand how safety is achieved or compromised in such a system

Dissemination of evidence-based standards of care.

Standards of care pertain to crafting and implementing patient-centered treatment interventions. Standards of care must take into consideration the patient's gender, ethnicity, medical and dental history, insurance coverage (or socioeconomic level, if a private patient), and the timeliness of the targeted scientific evidence. This resolves into a process by which clinical decision-making about the optimal patient-centered treatment relies on the best available research evidence, and all other necessary inputs and factors to provide the best possible treatment. Standards of care must be evidence-based, and not merely based on the evidence - the dichotomy being critical in contemporary health services research and practice. Evidence-based standards of care must rest on the best available evidence that emerges from a concerted hypothesis-driven process of research synthesis and meta-analysis. Health information technology needs to become an every-day reality in health services research and practice to ensure evidence-based standards of care. Current trends indicate that user-friendly methodologies, for the dissemination of evidence-based standards of care, must be developed, tested and distributed. They should include approaches for the quantification and analysis of the textual content of systematic reviews and of their summaries in the form of critical reviews and lay-language summaries

Traceability and Provenance in Big Data Medical Systems

Providing an appropriate level of accessibility to and tracking of data or process elements in large volumes of medical data, is an essential requirement in the Big Data era. Researchers require systems that provide traceability of information through provenance data capture and management to support their clinical analyses. We present an approach that has been adopted in the neuGRID and N4U projects, which aimed to provide detailed traceability to support research analysis processes in the study of biomarkers for Alzheimers disease, but is generically applicable across medical systems. To facilitate the orchestration of complex, large-scale analyses in these projects we have adapted CRISTAL, a workflow and provenance tracking solution. The use of CRISTAL has provided a rich environment for neuroscientists to track and manage the evolution of data and workflow usage over time in neuGRID and N4U.Comment: 6 pages, 3 diagrams. Proc of the 28th Int Symposium on Computer-Based Medical Systems (CBMS 2015) Sao Carlos, Brazil. June 2015. arXiv admin note: text overlap with arXiv:1502.0154