IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium最新文献

{"title":"Knowledge-based and knowledge-lean methods combined in unsupervised word sense disambiguation","authors":"Antonio Jimeno-Yepes, A. Aronson","doi":"10.1145/2110363.2110449","DOIUrl":"https://doi.org/10.1145/2110363.2110449","url":null,"abstract":"Word sense disambiguation (WSD) is an intermediate task within information retrieval and information extraction, attempting to select the proper sense of ambiguous words. For instance, the word cold could either refer to low temperature or viral infection.\u0000 Due to the scarcity of training data, knowledge-based and knowledge-lean methods receive attention as disambiguation methods. Knowledge-based methods compare the context of the ambiguous word to the information available in a terminological resource, but their main purpose is not word sense disambiguation. Knowledge-lean unsupervised methods rely on term distributions instead of a resource enumerating the possible senses but might be inappropriate when there is a requirement to commit to a terminological resource as a catalog for candidate senses.\u0000 We present preliminary results of the combination of knowledge-based and knowledge-lean unsupervised methods which improves the performance of knowledge-based methods between 3% and 8%. The evaluation is done on a new word sense disambiguation set which is available to the community.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"22 1","pages":"733-736"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74565843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PANI: an interactive data-driven tool for target prioritization in signaling networks","authors":"Huey-Eng Chua, S. Bhowmick, L. Tucker-Kellogg, Yingqi Wang, C. Dewey, Hanry Yu","doi":"10.1145/2110363.2110471","DOIUrl":"https://doi.org/10.1145/2110363.2110471","url":null,"abstract":"Biological network analysis often aims at the target identification problem, which is to predict which molecule to inhibit (or activate) for a disease treatment to achieve optimum efficacy and safety. A related goal, arising from the increasing availability of high-throughput screening (HTS), is to suggest many molecules as potential targets. The target prioritization problem is to predict a subset of molecules in a given disease-associated network which is likely to include successful drug targets. Sensitivity analysis prioritizes targets in a dynamic network model according to principled criteria, but fails to penalize off-target effects, and does not scale for large networks. In this demonstration, we present PANI(Putative TArget Nodes PrIoritization), a novel interactive system that addresses these limitations. It prunes and ranks the possible target nodes by exploiting concentration-time profiles and network structure (topological) information and visually display them in the context of the signaling network. Through the interactive user interface, we demonstrate various innovative features of PANI that enhance users' understanding of the prioritized nodes.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"11 1","pages":"851-854"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89907140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing clinical data in XML: bridging the gaps","authors":"Joshua Hui, S. Knoop, P. Schwarz","doi":"10.1145/2110363.2110469","DOIUrl":"https://doi.org/10.1145/2110363.2110469","url":null,"abstract":"As identified by recent US Dept. of Health and Human Services rulings [2], cohesive standards are essential to increasing accessibility and consumablity of data from heterogeneous sources. The ability to exchange standardized healthcare information is a critical aspect of this problem and HL7s XML-based Clinical Document Architecture (CDA) is quickly becoming the prevailing format. CDA has clear benefits for healthcare information exchange, but also introduces new technical challenges when one desires to perform in-depth analysis on the information captured by a set of these documents. Healthcare Information Warehouse for Analytics and Sharing (HIWAS), a tooling technology, addresses this challenge in two key ways: one, summarizing data for better understanding by a human user and, two, facilitating conventional analysis by aiding in the creation of and transformation to a simplified model. By making these complex XML documents digestible with conventional business intelligence and analysis technology, HIWAS lowers a key barrier to meaningful use of aggregated clinical data.\u0000 In this demonstration, we first describe challenges of integrating and analyzing CDA documents, how they are addressed by the HIWAS technology, and finally present an application scenario in which we prepare laboratory data captured in this standard format for analysis by public health officials.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"15 1","pages":"843-846"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86216454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modifying without a trace: general audit guidelines are inadequate for open-source electronic health record audit mechanisms","authors":"J. King, Benjamin H. Smith, L. Williams","doi":"10.1145/2110363.2110399","DOIUrl":"https://doi.org/10.1145/2110363.2110399","url":null,"abstract":"Without adequate audit mechanisms, electronic health record (EHR) systems remain vulnerable to undetected misuse. Users could modify or delete protected health information without these actions being traceable. The objective of this paper is to assess electronic health record audit mechanisms to determine the current degree of auditing for non-repudiation and to assess whether general audit guidelines adequately address non-repudiation. We derived 16 general auditable event types that affect non-repudiation based upon four publications. We qualitatively assess three open-source EHR systems to determine if the systems log these 16 event types. We find that the systems log an average of 12.5% of these event types. We also generated 58 black-box test cases based on specific auditable events derived from Certification Commission for Health Information Technology criteria. We find that only 4.02% of these tests pass. Additionally, 20% of tests fail in all three EHR systems. As a result, actions including the modification of patient demographics and assignment of user privileges can be executed without a trace of the user performing the action. The ambiguous nature of general auditable events may explain the inadequacy of auditing for non-repudiation. EHR system developers should focus on specific auditable events for managing protected health information instead of general events derived from guidelines.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"5 1","pages":"305-314"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86643130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting and using document structure in scientific text","authors":"A. Waard, S. Ananiadou, M. Martone, Ágnes Sándor, H. Shatkay","doi":"10.1145/2110363.2110482","DOIUrl":"https://doi.org/10.1145/2110363.2110482","url":null,"abstract":"The detection of discourse structure of scientific documents is important for a number of tasks, including biocuration efforts, text summarisation, and the creation of improved formats for scientific publishing. Currently, many parallel efforts exist to detect a range of discourse elements at different levels of granularity, and for different purposes, including extraction of information from complex documents, alignment of parallel corpora across languages, and support for document summarization (particularly multi-document summarization). Another interesting class of applications comes from \"bibliometrics\" and \"scientometrics\". For example, for analysis of argument structure in full text articles from the scientific literature, it may be important to know where a particular reference is cited or where a particular statement is made (Background, Discussion, etc.). Another application might include tracking over time where (in what sections) an entity or concept is mentioned, to determine whether the mentions migrate from research claims into the \"Background\" or eventually to the \"Methods\" sections of articles, as the concept moves from \"foreground\" (subject of the research) to \"background\". In this panel we would like to, explore compare, contrast and evaluate different scientific discourse annotation schemes and tools, in order to answer questions such as: What motivates a certain level, method, viewpoint for annotating scientific text? What is the annotation level for a unit of argumentation: an event, a sentence, a segment? What are advantages and disadvantages of all three? How easily can different schemes to be applied to texts? Are they easily trainable? Which schemes are most portable? Can they be applied to both full papers and abstracts? Can they be applied to texts in different domains? How granular should annotation schemes be? What are the advantages/disadvantages of fine and coarse grained annotation categories? What correlations occur among document structure, argumentation, and rhetorical functions? Is there a common framework that could be used for domain-independent document structure annotation?","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"21 1","pages":"883-884"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82473996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional temporal mining in clinical data","authors":"S. Tsumoto, S. Hirano","doi":"10.1145/2110363.2110426","DOIUrl":"https://doi.org/10.1145/2110363.2110426","url":null,"abstract":"Since medical and healthcare data include temporal trends of clinical symptoms, temporal data mining is one of the most important elements to discover knowledge. In this paper, we propose a three-dimensional trajectories mining method to capture the similarities between temporal trajectories of three selected variables. The method was evaluated on two datasets: one is on chronic hepatitis, and the other is on temporal trends of #orders in our university hospital. The results showed that, compared with conventional studies, the method gave more detailed classification of temporal trends.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"464 1","pages":"563-572"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83010131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated syndrome classification using early phase emergency department data","authors":"Deepika Mahalingam, Javed Mostafa, D. Travers, Stephanie W. Haas, A. Waller","doi":"10.1145/2110363.2110406","DOIUrl":"https://doi.org/10.1145/2110363.2110406","url":null,"abstract":"The primary motivation behind automated syndrome classification is to shorten the time it may take to detect an outbreak or a community-wide public health issue. State-of-the-art syndrome classification techniques have primarily used Emergency Department (ED) chief complaints (CCs) or other short free text descriptions of patient symptoms for near real-time surveillance purposes. We propose a system that can automatically classify an ED record with initial temperature, chief complaint and triage nurse's notes into one or more syndromes using the vector space model. Terms from syndrome definitions and a small tf-idf weighted syndrome-positive training set are used to create a reference dictionary for generating the syndrome and triage note vectors. Subsequently, cosine similarity between the vectors is used to establish the particular syndrome category. We tested the system on a manually classified dataset of 485 ED records for the gastro-intestinal (GI) syndrome and measured performance in terms of sensitivity (~93%) and specificity (~82%). Initial results show that this system is capable of producing a better balance between these measures compared to existing automatic syndrome categorization systems which use only chief complaints and/or diagnosis codes.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"43 1","pages":"373-378"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88416769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An event-based BSN middleware that supports seamless switching between sensor configurations","authors":"C. Seeger, A. Buchmann, Kristof Van Laerhoven","doi":"10.1145/2110363.2110420","DOIUrl":"https://doi.org/10.1145/2110363.2110420","url":null,"abstract":"Recent advances in wearable sensors have surged in novel fitness and preventive health care systems that measure step counts, activity levels, and performed exercises with inertial sensors, enabling users to monitor condition and day-to-day lifestyle. This paper presents a middleware designed for a smartphone unit to support health monitoring applications. Its event-driven architecture enables modular system design and seamless switching between sets of embedded sensors. The strengths of the middleware are highlighted in a deployed feasibility study where daily and gym activities are recognized through an interchangeable set of wireless sensors. The study demonstrates that the setup is suitable for daily usage with minimal impact on the phone's resources.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"5 1","pages":"503-512"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87857328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lessons learned from England's national electronic health record implementation: implications for the international community","authors":"K. Cresswell, A. Robertson, A. Sheikh","doi":"10.1145/2110363.2110441","DOIUrl":"https://doi.org/10.1145/2110363.2110441","url":null,"abstract":"Background: National electronic health record (EHR) programs are increasingly being pursued across the world with the aim of improving the safety, quality and efficiency of healthcare. Despite significant international investments, and particularly in the light of reported \"failures\", there is surprisingly little evidence on the specific and potentially transferable factors associated with the planning and execution of large-scale EHR implementations. England embarked on a National Program in 2002, characterized by \"top-down\", central procurement of a few, standardized EHR systems. Objectives: To evaluate the national implementation and adoption of EHRs in English hospitals and derive lessons for this and other national EHR programs. Design: We conducted a qualitative case study-based longitudinal evaluation drawing on sociotechnical principles. Setting: Data were collected from 12 \"early adopter\" hospitals across England. Data sources: Our dataset consisted of 431 semi-structured interviews; 590 hours of observations; 334 sets of notes from observations, researcher field notes and notes from conferences; 809 hospital documents; and 58 national and regional documents. Results: A range of factors emerged as important. These included software characteristics and user involvement in shaping technology; realistic timelines, balancing the national EHR vision and stakeholder expectations; relationship building and communication; balancing national progress with allowing local accommodation; and maintaining central direction whilst permitting degrees of local autonomy. Conclusions: It is not possible to be prescriptive for achieving \"successful\" national EHR implementations. Nonetheless, we identify dimensions likely to be of greater significance than others, in a range of national contexts. We argue that design, based on users' requirements, and accommodation of the technology in the healthcare setting need to occur on a small-scale first before building out to satisfy organizational, local health economy and national needs, and that this needs time. Our results will we hope offer evidence to inform national strategies for large-scale and expensive EHR ventures.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"38 1","pages":"685-690"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73743151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public health community mining in YouTube","authors":"Scott H. Burton, Richard G. Morris, Michael Dimond, Joshua A. Hansen, C. Giraud-Carrier, J. West, C. Hanson, Michael D. Barnes","doi":"10.1145/2110363.2110376","DOIUrl":"https://doi.org/10.1145/2110363.2110376","url":null,"abstract":"YouTube has become a vast repository of not only video content, but also of rich information about the reactions of viewers and relationships among users. This meta-data offers novel ways for public health researchers to increase their understanding of, and ultimately to more effectively shape, people's attitudes and behaviors as both consumers and producers of health. We illustrate some of the possibilities here by showing how communities of videos, authors, subscribers and commenters can be extracted and analyzed. Tobacco use serves as a case study throughout.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"33 1","pages":"81-90"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73729204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}