The growing consensus that most valuable data source for biomedical discoveries is derived from human samples is clearly reflected in the growing number of translational medicine and translational sciences departments across pharma as well as academic and government supported initiatives such as Clinical and Translational Science Awards (CTSA) in the US and the Seventh Framework Programme (FP7) of EU with emphasis on translating research for human health.

Overweight and obesity have become a global problem. Health professionals are poorly prepared in weight management, which has an effect on their attitudes and management skills with regard to overweight and obese patients.Aim and setting: To assess the knowledge, attitudes and management skills of medical practitioners regarding weight management at Odi District Hospital, Gauteng Province, South Africa.

Background: Opportunities to use data and information to address challenges in international agricultural research and development are expanding rapidly. The use of agricultural trial and evaluation data has enormous potential to improve crops and management practices. However, for a number of reasons, this potential has yet to be realized. This paper reports on the experience of the AgTrials initiative, an effort to build an online database of agricultural trials applying principles of interoperability and open access. Methods: Our analysis evaluates what worked and what did not work in the development of the AgTrials information resource. We analyzed data on our users and their interaction with the platform. We also surveyed our users to gauge their perceptions of the utility of the online database. Results: The study revealed barriers to participation and impediments to interaction, opportunities for improving agricultural knowledge management and a large potential for the use of trial and evaluation data.  Conclusions: Technical and logistical mechanisms for developing interoperable online databases are well advanced.  More effort will be needed to advance organizational and institutional work for these types of databases to realize their potential.

This research aimed to investigate the effects of knowledge management enablers, such as organizational structure, leadership, learning, information technology systems, trust, and collaboration, on the knowledge management process of creation, storage, sharing, and application.

In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical resources and provide treatment programs. The technique we applied is referred to as KG-based recommendation system. When several experiments have been carried out, it is demonstrated that it is more intelligent and precise in disease prediction and treatment recommendation, similar to the state of the art. Also, it works well in the accuracy and comprehension, which is much higher and highly consistent with the predictions of the theoretical model. The fact that our work involves studies of multitask healthcare management recommendation system, which can contribute to the smart healthcare development, proves to be promising and encouraging.

To evaluate the level and identify predictors of nursing students' knowledge and attitudes of pain management.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy.

To control disease, laboratories and providers are required to report conditions to public health authorities. Reporting logic is defined in a variety of resources, but there is no single resource available for reporters to access the list of reportable events and computable reporting logic for any jurisdiction. In order to develop evidence-based requirements for authoring such knowledge, we evaluated reporting logic in the Council of State and Territorial Epidemiologist (CSTE) position statements to assess its readiness for automated systems and identify features that should be considered when designing an authoring interface; we evaluated codes in the Reportable Condition Mapping Tables (RCMT) relative to the nationally-defined reporting logic, and described the high level business processes and knowledge required to support laboratory-based public health reporting. We focused on logic for viral hepatitis. We found that CSTE tabular logic was unnecessarily complex (sufficient conditions superseded necessary and optional conditions) and was sometimes true for more than one reportable event: we uncovered major overlap in the logic between acute and chronic hepatitis B (52%), acute and Past and Present hepatitis C (90%). We found that the RCMT includes codes for all hepatitis criteria, but includes addition codes for tests not included in the criteria. The proportion of hepatitis variant-related codes included in RCMT that correspond to a criterion in the hepatitis-related position statements varied between hepatitis A (36%), acute hepatitis B (16%), chronic hepatitis B (64%), acute hepatitis C (96%), and past and present hepatitis C (96%). Public health epidemiologists have the need to communicate parameters other than just the name of a disease or organism that should be reported, such as the status and specimen sources. Existing knowledge resources should be integrated, harmonized and made computable. Our findings identified functionality that should be provided by future knowledge management systems to support epidemiologists as they communicate reporting rules for their jurisdiction.

Knowledge management as a field is concerned with the management of knowledge, including the management of knowledge in research processes. Knowledge management theory has the potential to support research into problems such as HIV, antibiotic resistance and others, particularly in terms of aspects of scientific research related to the contribution of social science. To date, however, these challenges remain with us, and theoretical contributions that can complement natural science efforts to eradicate these problems are needed. This paper seeks to offer a theoretical contribution grounded in Kuhn's paradigm theory of innovation, and in the argument by Lakatos that scientific research can be fundamentally non-innovative, which suggests that social science aspects of knowledge creation may hold the key to more effective biomedical innovation. Given the consequences of ongoing and emerging global crises, and the failure of knowledge systems of scientific research to solve such problems outright, this paper provides a review of theory and literature arguing for a new paradigm in scientific research, based on the development of global systems to maximise research collaborations. A global systems approach effectively includes social science theory development as an important complement to the natural sciences research process. Arguably, information technology and social media technology have developed to the point at which solutions to knowledge aggregation challenges can enable solutions to knowledge problems on a scale hitherto unimaginable. Expert and non-expert crowdsourced inputs can enable problem-solving through exponentially increasing problem-solving inputs, using the 'crowd,' thereby increasing collaborations dramatically. It is argued that these developments herald a new era of participatory research, or a democratisation of research, which offers new hope for solving global social problems. This paper seeks to contribute to this end, and to the recognition of the important role of social theory in the scientific research process.

The ultimate goal of knowledge translation and exchange (KTE) activities is to facilitate incorporation of research knowledge into program and policy development decision making. Evidence-informed decision making involves translation of the best available evidence from a systematically collected, appraised, and analyzed body of knowledge. Knowledge management (KM) is emerging as a key factor contributing to the realization of evidence-informed public health decision making. The goal of health-evidence.ca is to promote evidence-informed public health decision making through facilitation of decision maker access to, retrieval, and use of the best available synthesized research evidence evaluating the effectiveness of public health interventions.

To identify current evidence on health care managers' competence in knowledge management.

To select, present and summarize some of the best papers in the field of Knowledge Representation and Management (KRM) published in 2020.

Background: Higher education institutions include experts who are knowledgeable. Knowledge management facilitates institutions to enhance the capacity to collect information and knowledge and apply it to problem-solving and decision making. Through the review of related studies, we observed that there are multiple concepts and terms in the field of knowledge management. Thus, the complexity and variety of these concepts and definitions must be clarified. Considering the importance of clarifying these concepts for utilization by users, this study aimed to examine the concepts related to this filed. Methods: The methodology used in this study was based on the Carnwell and Daly's critical review method. An extensive search was carried out on various databases and libraries. A critical and profound review was carried out on selected articles. Many wandering concepts were found. Identified concepts were classified into seven categories based on conceptual proximity. Existing definitions and evidence in relation to extracted concepts were criticized and synthesized. The definitional attributes for them were identified and a conceptual identity card was provided for each of the concepts. Results: Thirty-seven concepts with the most relevance to the field of knowledge management were extracted. There was no clear boundary among them, and they wandered. To avoid more confusion, concepts were classified according to semantic relation. Eight categories were created; each category consisted of a mother concept and several other concepts with similarity and proximity to the meaning of the original concept. Their attributes have been identified, and finally, each of them was presented in the form of a conceptual identity card. Conclusion: Through critically reviewing the literature in this field, we were able to identify the concepts and realize their attributes. In this way, we came to a new interpretation of the concepts. At the end of the study, we concluded that some of the concepts have not been properly defined and are not properly located in the knowledge management field; also their application is uncertain.

Self-management is increasingly recognized as an important method through which individuals with bipolar disorder (BD) may cope with symptoms and improve quality of life. Digital health technologies have strong potential as a method to support the application of evidence-informed self-management strategies in BD. Little is known, however, about how to most effectively maximize user engagement with digital platforms.

Dengue has emerged as a major public health problem in Bhutan, with increasing incidence and widening geographic spread over recent years. This study aimed to investigate the knowledge and clinical management of dengue among medical practitioners in Bhutan.

Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base.

Knowledge is considered to be an important resource; it is the source of competitive advantage. However, if knowledge is managed well with Knowledge Management (KM), then it becomes a source for sustainable competitive advantage for organizations. If KM is implemented in an organization, it would improve the organizational competitiveness, performance, and productivity, and facilitate the efficient use of resources. Due to intense competition in the global market, many organizations are moving towards the adoption of KM. The healthcare sectors of many developed countries have moved towards the implementation of KM because it can improve the procuring of knowledge from ongoing activities by the effective use of data repositories. Developing countries have now realized the potential and benefits of KM adoption. Pakistan is one of the developing countries that have recently shown an inclination towards the adoption of KM in its healthcare sector to improve performance of its healthcare. This study was composed of two main research phases. Firstly, the enablers of KM were reviewed from earlier studies. Secondly, interpretive structural modeling (ISM) and MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) techniques were used to show the interrelationships between KM enablers and driving and dependence power of each enabler. The application of ISM and MICMAC technique shows that policy incentive, long-term strategic planning, Information Technology (IT), and alignment of KM efforts with business strategy are the main enablers of KM adoption in the healthcare of Pakistan. Focusing on the identified enablers will help in the implementation of KM. Policy incentives can work as a catalyst to promote KM adoption in the healthcare of Pakistan.

Business and practice management principles are critical components of healthcare provision. Business and practice management is currently undertaught in plastic surgery training programs. The objective was to assess the status of business and practice management teaching amongst plastic surgery programs in Canada. An online survey of all enrolled plastic surgery residents was conducted in 2019 to 2020. Participants were invited to rate their knowledge and confidence about core principles in business and practice management. Sixty-five out of 126 residents responded to this survey (response rate, 51.6%). Only 7.8% of participants had previous business and practice management training; 23.1% reported receiving training in business and practice management during their residency. Participants reported a low level of knowledge and confidence in business and practice management (average Likert score between 3 and 4). Participants reported a high desire for future training in business and practice management particularly in billing and coding (91.2%) and business operations (91.2%). Plastic surgery residents in Canada reported a low level of knowledge and confidence about business and practice management. They desire the inclusion of business and practice management training in future curriculum.

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.