Developing a Novel Ontology for Cybersecurity in Internet of Medical Things-Enabled Remote Patient Monitoring.

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. IoMT is a collection of various medical devices and their applications within the research domain. On the other hand, MIoT ontology refers to the proposed ontology that defines various concepts, roles, and individuals. MIoT ontology utilizes the knowledge engineering methodology outlined in Ontology Development 101, along with the structured life cycle, and establishes semantic interoperability among medical devices to secure IoMT assets from vulnerabilities and cyberattacks. By defining key concepts and relationships, it becomes easier to understand and analyze the complex network of information within the IoMT. The MIoT ontology captures essential key terms and security-related entities for future extensions. A conceptual model is derived from the MIoT ontology and validated through a case study. Furthermore, this paper outlines a roadmap for future research, highlighting potential impacts on security automation in healthcare applications.

Analytical quality by design based on knowledge organization: A case study of developing an ultrahigh-performance liquid chromatography method for the detection of phenolic compounds.

INTRODUCTION: Despite numerous successful cases, there are still some challenges in using analytical quality by design (AQbD) for the development of analytical methods. Knowledge organization helps to enhance the objectivity of risk assessment, reduce the number of preliminary exploratory experiments, identify potential critical method parameters (CMPs) and their scope. OBJECTIVE: In the present study, we aimed to develop a simple, rapid, and robust analytical method for detecting phenolic compounds in Xiaochaihu capsule intermediates utilizing knowledge organization. METHODS: Knowledge organization and AQbD were combined to obtain the initial analytical conditions through knowledge collection, extraction, reorganization, and analysis. The quantitative relationship between critical method attributes (CMAs) and CMPs was then established by a definitive screening design. The method operable design region was calculated using an exhaustive Monte Carlo approach based on the probability of reaching the standard. Robustness investigation and methodological validation were finally performed. RESULTS: Analytical target profiles, CMAs, potential CMPs, and initial analytical conditions were initially identified, and the optimized ranges of operating parameters were obtained. A UHPLC method was successfully established for the analysis of phenolic compounds in ginger-ginger pinellia percolate, and the method validation outcomes were also satisfactory. CONCLUSION: The developed method can be a reliable means to detect the phenolic compounds of Xiaochaihu capsule intermediates. Knowledge organization provides a new approach for making better use of prior knowledge, significantly enhancing the efficiency of analytical method development. The approach is versatile and can be similarly applied to the development of other methods.

The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model.

The increasing prevalence of multimorbidity requires new theoretical models and educational approaches to develop physicians' ability to manage multimorbidity patients. The Health Issues Network (HIN) is an educational approach based on a graphical depiction of the evolutions over time of the concurrent health issues of a patient and of their interactions. From a theoretical point of view, the HIN approach is rooted in Prigogine's vision of the "becoming" of the events and in the concept of knowledge organization, intended as the process of storing and structuring of information in a learner's mind. The HIN approach allows to design clinical exercises to foster learners' ability to detect evolutionary paths and interactions among health issues. Recent findings of neuroscience support the expectation that interpreting, completing, and creating diagrams depicting complex clinical cases improves the "sense of time", as a fundamental competence in the management of multimorbidity. The application of the HIN approach is expected to decrease the risk of errors in the management of multimorbidity patients. The approach is still under validation, both for undergraduate students and for the continuous professional development of physicians.

Tourism-type ontology framework for tourism-type classification, naming, and knowledge organization.

The names of tourism types formed by scholars and practitioners reflect the connotations of various tourism types from different aspects and carry a wealth of tourism knowledge. The documents containing the names and connotations of 232 tourism types were sorted from the Springer Encyclopedia of Tourism and 16 major international academic journals. These documents were analyzed using the coding method of grounded theory. A total of 155 naming elements, 22 subcategories, and six categories were extracted. These naming elements, subcategories, and categories constitute the tourism-type ontology, which is the first tourism-type classification framework. Furthermore, the construction of tourism-type ontology enriches the existing research on overall tourism knowledge. The tourism-type ontology can also be used as a preliminary framework for organizing overall tourism knowledge and a foundation for constructing a unified tourism-type naming rule.

Problem representation and diagnostic accuracy during an OSCE.

PURPOSE: The National Academy of Medicine has called for "identifying opportunities to improve the diagnostic process". We studied the association between problem representation and diagnostic accuracy during an objective structured clinical exam (OSCE). MATERIALS AND METHODS: We conducted a non-randomized controlled trial during a ten-case OSCE. We measured whether a summary statement prompt increased the likelihood that the student listed the correct diagnosis and whether better summary statements were correlated with diagnostic accuracy. RESULTS: 114 students provided 1135 responses. The non-prompted control group yielded 631 responses, listing the correct diagnosis first 73% of the time and within the top three slots 85% of the time. The intervention group exposed to the prompt yielded 453 responses listing the correct diagnosis first 72% of the time (P = 0.617) and within the top three slots 84% of the time (P = 0.760). Summary statements were scored on a 0, 0.5, or 1 rubric. When grouped according to summary statement score, students listed the correct diagnosis first 74%, 70%, and 72% of the time respectively (P = 0.666). The correct diagnosis was included within the top three slots 88%, 82%, and 83% of the time (P = 0.238). CONCLUSIONS: Prompting students to form a summary statement did not improve diagnostic accuracy. Better summary statements were not correlated with diagnostic accuracy.

An Empirical Study on Talent Management Strategies of Knowledge-Based Organizations Using Entrepreneurial Psychology and Key Competence.

The empirical study reported here aims to improve the effectiveness of knowledge-based talent management in science and technology enterprises and promote the stable development of enterprises. First, the impact of entrepreneurs' psychological cognition and personal characteristics on entrepreneurial activities is analyzed based on entrepreneurial psychology. Then, the theory of key competence is introduced to study the management mode of knowledge-based talents. The advantages of talents in enterprises are sorted out through constructing the key competency model to manage talents efficiently. The technology-based enterprise M is taken as an example for analysis by the key competence model to obtain 18 key capability indexes. Through the principal component analysis of 255 employees' survey results, finally, four factors are extracted (business execution ability, team cooperation ability, strategic thinking ability, and management decision-making ability), which can reflect 68.92% of the total key competence. The average values of "business execution ability" and "team cooperation ability" in the first-level dimension of key competence index are 4.14 and 4.24, respectively, which can be regarded as the essential key competence. The investigation results of the academic qualifications of staff of M indicate that 6% of employees have a doctorate, 38% have a master's degree, 37% have a Bachelor's degree, and 19% have a junior college degree or below. Moreover, knowledge-based employees are basically satisfied with the organization and management of the company, but they are dissatisfied with the training mechanism and promotion mechanism. Therefore, enterprises should pay attention to the psychological needs of knowledge workers and the innovation of talent management. The research results are of significant value for science and technology enterprises to absorb and retain knowledge-based talents and promote the common development of enterprises and employees.

The carbon footprint of a knowledge organization and emission scenarios for a post-COVID-19 world.

The looming climate crisis requires an immediate response, in which organizations, as major contributors, should play a central role. However, these organizations need appropriate tools to measure and mitigate their climate impacts. One commonly applied method is carbon footprint analysis. Carbon footprint analyses have been conducted for various types of organizations, but knowledge organizations, such as universities and research institutes, have received far less attention, because their carbon footprint is often less visible and can be easily underestimated. This study is based on the carbon footprint analysis of one multinational knowledge organization. This analysis then helped identify the major sources of climate impacts in other such knowledge organizations. These are mainly indirect emissions (Scope 3) and to a large extent (79%) travel-related emissions. Based on these findings, three scenarios for a post-COVID-19 world were developed and analyzed. The results from the first two scenarios showed that despite a reduction in business travel and employees working from home, Scope 3 and travel-related emissions would remain the largest contributor. Only in the unlikely case of the third, non-recovery scenario did the share of travel-related emissions drop, turning heating into the largest contributor. In addition to measuring the carbon footprint, the study discusses potential mitigation strategies knowledge organizations could apply to reduce their carbon footprint. The focus is on how to avoid and reduce emissions, but new forms of carbon offsetting are also addressed. Based on the findings, a mitigation policy framework and recommendations for further research are proposed.

Detection of medications associated with Alzheimer's disease using ensemble methods and cooperative game theory.

OBJECTIVE: To study the feasibility of evaluating feature importance with Shapley Values and ensemble methods in the context of pharmacoepidemiology and medication safety. METHODS: We detected medications associated with Alzheimer's disease (AD) by examining the additive feature attribution with combined approach of Gradient Boosting and Shapley Values in the Medication use and Alzheimer's disease (MEDALZ) study, a nested case-control study of 70,719 verified AD cases in Finland. Our methodological approach is to do binary classification using Gradient boosting (an ensemble of weak classifiers) in a supervised learning manner. Then we apply Shapley Values (from cooperative game theory) to analyze how feature combinations affect the classification result. Medication use with a five to one year time-window before AD diagnosis was ascertained from Prescription register. RESULTS: Antipsychotics with low or medium dose, antidepressants with medium to high dose, and cardiovascular medications with medium to high dose were identified as the contributing features for separating cases with AD from controls. Medium to high amount of irregularity in the purchase pattern were an indicating feature for separating AD cases from controls. The similarity of medication purchases between AD cases and controls made the feature evaluation challenging. CONCLUSIONS: The combined approach of Gradient Boosting and feature evaluation with Shapley Values identified features that were consistent with findings from previous hypothesis-driven studies. Additionally, the results from the additive feature attribution identified new candidates for future studies on AD risk factors. Our approach also shows promise for studies based on observational studies, where feature identification and interactions in populations are of interest; and the applicability of using Shapley Values for evaluating feature relevance in pattern recognition tasks.

Taxonomías digitales: fundamentos teóricos y metodología de construcción / Digital taxonomies: theoretical fundamentals and construction methodology

Resumen El artículo analiza las taxonomías digitales desde la perspectiva bibliotecológica. Su objetivo fue construir una taxonomía digital del área de conocimiento "Sistema solar" que pudiera ser implementada como sistema de acceso temático jerárquico-visual para un conjunto de recursos de información digitales albergados en un sitio web. La metodología empleada en la construcción de la taxonomía consistió en una propuesta particular que se nutre de dos metodologías relevantes sobre el tema. Se encontró que las taxonomías son un Sistema para la Organización del Conocimiento (SOC) que, debido a su potencial representador y organizador, han migrado al espacio de los Sistemas para la Organización del conocimiento en Red (SOCR) cuyas funciones en la web están asociadas, entre muchas aplicaciones, a la indización y clasificación de recursos de información. Se concluye que el conocimiento teórico y aplicado de las taxonomías digitales es prioritario para los profesionales de la información que día a día se enfrentan a más retos relacionados con el ordenamiento de recursos de información insertos en la World Wide Web.

Abstract The article analyzes digital taxonomies from the librarianship perspective. Its objective was to build a digital taxonomy about "Solar System" knowledge area that can be implemented as hierarchical-visual subject access system for a set of digital information resources stored in a website. The methodology used to build the taxonomy was a proposal based on two relevant methodologies about the topic. It was found that taxonomies are a Knowledge Organization Systems (KOS) that, due to its representational and organizer potential, have migrated to the space of Networked Knowledge Organization Systems (NKOS), whose tasks on the web are associated, among many applications, to the indexing and classification of information resources. It is concluded that the theoretical and applied knowledge of digital taxonomies is a priority for information professionals who every day deals with challenges related to the organization of information sources inserted in the World Wide Web.

Statistical regularities shape semantic organization throughout development.

Our knowledge about the world is represented not merely as a collection of concepts, but as an organized lexico-semantic network in which concepts can be linked by relations, such as "taxonomic" relations between members of the same stable category (e.g., cat and sheep), or association between entities that occur together or in the same context (e.g., sock and foot). To date, accounts of the origins of semantic organization have largely overlooked how sensitivity to statistical regularities ubiquitous in the environment may play a powerful role in shaping semantic development. The goal of the present research was to investigate how associations in the form of statistical regularities with which labels for concepts co-occur in language (e.g., sock and foot) and taxonomic relatedness (e.g., sock and pajamas) shape semantic organization of 4-5-year-olds and adults. To examine these aspects of semantic organization across development, we conducted three experiments examining effects of co-occurrence and taxonomic relatedness on cued recall (Experiment 1), word-picture matching (Experiment 2), and looking dynamics in a Visual World paradigm (Experiment 3). Taken together, the results of the three experiments provide evidence that co-occurrence-based links between concepts manifest in semantic organization from early childhood onward, and are increasingly supplemented by taxonomic links. We discuss these findings in relation to theories of semantic development.

Implications of Knowledge Organization Systems for Health Information Exchange and Communication during the COVID-19 Pandemic.

This article aims to review the important roles of health knowledge organization systems (KOSs) during the COVID-19 pandemic. Different types of knowledge organization systems, including term lists, synonym rings, thesauri, subject heading systems, taxonomies, classification schemes, and ontologies are widely recognized and applied in both modern and traditional information systems. Apart from their usage in the management of data, information, and knowledge, KOSs are seen as valuable components for large information architecture, content management, findability improvement, and many other applications. After introducing the challenges of information overload and semantic conflicts, the article reviews the efforts of major health KOSs, illustrates various health coding schemes, explains their usages and implementations, and reveals their implications for health information exchange and communication during the COVID-19 pandemic. Some general examples of the applications, services, and analysis powered by KOSs are presented at the end. As revealed in this article, they have become even more critical to aid the frontline endeavors to overcome the obstacles due to information overload and semantic conflicts that can occur during devastating historic and worldwide events like the COVID-19 pandemic.

Critical process parameter identification of manufacturing processes of Astragali Radix extract with a weighted determination coefficient method.

Objective: Critical process parameters (CPPs) identification is an important step of the implementation of quality by design (QbD) concept. There are many CPP identification methods, such as risk analysis method, sensitivity analysis method, multiple linear regression method, standard partial regression coefficient (SPRC) method, and so on. The SPRC method can consider multiple process critical quality attributes (CQAs) simultaneously, but the determination of CPP number is subjective. Therefore, new CPP identification method is still required. Methods: The manufacturing process of Astragali Radix extract, which contained water reflux extraction, concentration, and ethanol precipitation, was used as an example. First, the multiple process CQAs were determined to be the yield of pigment, dry matter, sugars, and active ingredients. Second, the potential CPPs were determined by a knowledge organization method. Plackett-Burman designed experiments were then performed. A weighted determination coefficient ( R w 2 ) method was presented to identify CPPs. In this method, the importance of different CQAs was considered. Process parameters were removed one-by-one according to their importance index. The decrease in R w 2 was used to characterize the importance of the removed parameter. If the decrease of R w 2 was less than a preset threshold, the removed parameter was not a CPP. Results: During the manufacturing process of Astragali Radix extract, the potential CPPs determined by the knowledge organization method were water consumption, reflux extraction time, extraction frequency, ethanol content, ethanol consumption, and concentration endpoint. Reflux extraction time, the first ethanol consumption, the second ethanol consumption, and the second ethanol precipitation refrigeration temperature were found to be CPPs using the weighted determination coefficient method with the threshold of 10%. Conclusion: Using the weighted determination coefficient method, CPPs can be determined with all the CQAs considered based on their importance. The determination of CPP number is more objective compared with the SPRC method.

Critical process parameter identification of manufacturing processes of Astragali Radix extract with a weighted determination coefficient method / 中草药·英文版

Objective: Critical process parameters (CPPs) identification is an important step of the implementation of quality by design (QbD) concept. There are many CPP identification methods, such as risk analysis method, sensitivity analysis method, multiple linear regression method, standard partial regression coefficient (SPRC) method, and so on. The SPRC method can consider multiple process critical quality attributes (CQAs) simultaneously, but the determination of CPP number is subjective. Therefore, new CPP identification method is still required. Methods: The manufacturing process of Astragali Radix extract, which contained water reflux extraction, concentration, and ethanol precipitation, was used as an example. First, the multiple process CQAs were determined to be the yield of pigment, dry matter, sugars, and active ingredients. Second, the potential CPPs were determined by a knowledge organization method. Plackett-Burman designed experiments were then performed. A weighted determination coefficient (Rw2) method was presented to identify CPPs. In this method, the importance of different CQAs was considered. Process parameters were removed one-by-one according to their importance index. The decrease in Rw2 was used to characterize the importance of the removed parameter. If the decrease of Rw2 was less than a preset threshold, the removed parameter was not a CPP. Results: During the manufacturing process of Astragali Radix extract, the potential CPPs determined by the knowledge organization method were water consumption, reflux extraction time, extraction frequency, ethanol content, ethanol consumption, and concentration endpoint. Reflux extraction time, the first ethanol consumption, the second ethanol consumption, and the second ethanol precipitation refrigeration temperature were found to be CPPs using the weighted determination coefficient method with the threshold of 10%. Conclusion: Using the weighted determination coefficient method, CPPs can be determined with all the CQAs considered based on their importance. The determination of CPP number is more objective compared with the SPRC method.

"The 2-Dimensional Approach": a novel tool to help learners organize their knowledge and improve their clinical reasoning skills.

This article was migrated. The article was marked as recommended. Background: Clinical reasoning is an essential competence of a physician. Particularly, pathophysiological understanding is the key for novices to organize their knowledge and improve clinical reasoning. To this end, we propose a "2-Dimensional (2D) Approach" that visualizes pathophysiology by using a matrix of organs and systems. Methods: This study was a prospective observational study of 100 residents (PGY-1), who attended a lecture on the 2D Approach. They underwent a pre- and post-test that assessed their ability to list differentials for various symptoms and to choose the most likely diagnosis for a case vignette. We stratified the participants according to their baseline knowledge level on the pretest into 2 groups (high-knowledge and low-knowledge). In each of the 2 groups, we compared the change in the pre- and post-test scores between participants who used the 2D Approach during the posttest and those who did not. Results: In the high-knowledge group (n=59), the change in the pre- and post-test scores was significantly larger in the 2D Approach users than non-users (p=0.046), while in the low-knowledge group (n=41), there was no significant difference in the change of the scores between the 2D Approach users and non-users. Conclusions: On condition that residents have sufficient knowledge, the 2D Approach helps them organize their knowledge and improve their clinical reasoning skills, through visualization of pathophysiology on a matrix of organs and systems.

Rapid, experience-related changes in the organization of children's semantic knowledge.

The organization of knowledge according to relations between concepts is crucially important for many cognitive processes, and its emergence during childhood is a key focus of cognitive development research. Prior evidence about the role of learning and experience in the development of knowledge organization primarily comes from studies investigating differences between preexisting, naturally occurring groups (e.g., children from rural vs. urban settings, children who own a pet vs. children who do not) and a handful of studies on the effects of researcher-developed educational interventions. However, we know little about whether knowledge organization can be relatively rapidly molded by shorter-term real-world learning experiences (e.g., on a timescale of days vs. years or months). The current study investigated whether naturalistic learning experiences can drive rapid measurable changes in knowledge organization in children by investigating the effects of a week-long zoo summer camp (compared with a control school-based camp) on the degree to which 4- to 9-year-old children's knowledge about animals was organized according to taxonomic relations. Although there were no differences in taxonomic organization between the zoo camp and the school-based camp at pretest, only children who participated in the zoo camp showed increases in taxonomic organization at posttest. Moreover, analyses of changes in taxonomic organization in zoo camp children suggested that these changes were primarily driven by improvements in the degree to which children differentiated between taxonomic categories. These findings provide novel evidence that naturalistic experiences can drive rapid changes in knowledge organization.

The User Knows What to Call It: Incorporating Patient Voice Through User-Contributed Tags on a Participatory Platform About Health Management.

BACKGROUND: Body listening, described as the act of paying attention to the body's signals and cues, can be an important component of long-term health management. OBJECTIVE: The aim of this study was to introduce and evaluate the Body Listening Project, an innovative effort to engage the public in the creation of a public resource-to leverage collective wisdom in the health domain. This project involved a website where people could contribute their experiences of and dialogue with others concerning body listening and self-management. This article presents an analysis of the tags contributed, with a focus on the value of these tags for knowledge organization and incorporation into consumer-friendly health information retrieval systems. METHODS: First, we performed content analysis of the tags contributed, identifying a set of categories and refining the relational structure of the categories to develop a preliminary classification scheme, the Body Listening and Self-Management Taxonomy. Second, we compared the concepts in the Body Listening and Self-Management Taxonomy with concepts that were automatically identified from an extant health knowledge resource, the Unified Medical Language System (UMLS), to better characterize the information that participants contributed. Third, we employed visualization techniques to explore the concept space of the tags. A correlation matrix, based on the extent to which categories tended to be assigned to the same tags, was used to study the interrelatedness of the taxonomy categories. Then a network visualization was used to investigate structural relationships among the categories in the taxonomy. RESULTS: First, we proposed a taxonomy called the Body Listening and Self-Management Taxonomy, with four meta-level categories: (1) health management strategies, (2) concepts and states, (3) influencers, and (4) health-related information behavior. This taxonomy could inform future efforts to organize knowledge and content of this subject matter. Second, we compared the categories from this taxonomy with the UMLS concepts that were identified. Though the UMLS offers benefits such as speed and breadth of coverage, the Body Listening and Self-Management Taxonomy is more consumer-centric. Third, the correlation matrix and network visualization demonstrated that there are natural areas of ambiguity and semantic relatedness in the meanings of the concepts in the Body Listening and Self-Management Taxonomy. Use of these visualizations can be helpful in practice settings, to help library and information science practitioners understand and resolve potential challenges in classification; in research, to characterize the structure of the conceptual space of health management; and in the development of consumer-centric health information retrieval systems. CONCLUSIONS: A participatory platform can be employed to collect data concerning patient experiences of health management, which can in turn be used to develop new health knowledge resources or augment existing ones, as well as be incorporated into consumer-centric health information systems.

"Challenges and opportunities for medical library in ""Healthy China"" strategy" / 中华医学图书情报杂志

In order to have a better understanding of the role of medical library in medical information service during the implementation of Healthy China strategy,the need of health information service of the public and medical scientific researchers in implementation of Healthy China strategy were analyzed by outlining the development history and major targets of Healthy China strategy,and how to meet the requirements of the development of Healthy China for medical library was studies,namely by improving its resources development,service patterns and staff construction according to the present situation of big data development,the challenges medical library is faced in users needs,resources,platform,space,professionals and funds,and the opportunities brought about by the expanding requirements,improving information academic level,advancing new technologies,favorable policies and environments with relevant suggestions put forward.

Discussion about the application of topic maps technology on knowledge organization of traditional Chinese medicine with the example ofShanghanlun / 国际中医中药杂志

Literature of TCM contains abundant information of Chinese medicine. Traditional Chinese medicine information is characterized by its high degree of knowledge-intensive and complex inter-knowledge, so it is difficult to integrate and share knowledge. TheShanghanlun is one of the Chinese medical classics, and it includes the rules and methods of syndrome differentiation and treatment and it showed good effects in the clinical application. However, it is difficult to master for beginners. As a kind of knowledge organization tool, topic maps can flexibly define the relationship between knowledge, which realizes the visualization of knowledge network, and integrates and shares the distributed knowledge. This paper focused on the current situation of topic maps researches. The topic maps was used to organize the original content ofShanghanlun, construct the concept model of it and explore the specific application of topic maps technology in the field of traditional Chinese medicine.

Design and Realization of Tools for Ontology Construction / 医学信息学杂志

The paper begins with the ontology construction requirements based on ontology reuse and transformation of existing resources,combines the current situations of study on technical progress and tools for ontology construction at home and abroad,and conducts code development of tools for ontology construction and function realization based on WebProtege class library.In the process of realization,pay attention to the interactive mode of combination of automatic tool processing and manual review,and collect specific sample data to verify the feasibility and usability of applying the developed tools for ontology construction.

Construction of semantic relations of the top-level ontology of military medicine / 军事医学

Objective To explore a construction method of semantic relations of the top-level ontology of military medicine in order to construct the top-level ontology semantic network.Methods The military medical corpus was selected,and the relationships between the concepts were extracted using text analysis.On the basis of inheriting the semantic relations of UMLS,the special semantic relations of military medicine were added.Results A method of establishing the semantic relations of the top-level ontology of military medicine was proposed,the applicability of which was verified by example of the branch of military medical equipment.Conclusion The proposed method is effective and feasible,which can provide important support to the establishment of top-level semantic networks of military medicine.