{"title":"Electronic whiteboards in emergency medicine: a systematic review","authors":"Rasmus Rasmussen","doi":"10.1145/2110363.2110418","DOIUrl":"https://doi.org/10.1145/2110363.2110418","url":null,"abstract":"As more and more Emergency Departments replace the manual dry-erase whiteboards used for coordination of patient care and communication among clinicians with IT-based electronic whiteboards a need to clarify the effects of implementing these systems arises. This paper seeks to answer this question by systematically reviewing studies on electronic whiteboards. The results of the review indicate that electronic whiteboards influence the work at Emergency Departments in various different ways e.g. changes to work practice and changes to whiteboard information accuracy. Also, the review finds that there are mediating factors that have an impact upon these effects e.g. display format and integration with other clinical IT systems. However, the results are somewhat inconclusive and of a mixed nature and therefore this paper calls for more focused and specific research.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"14 1","pages":"483-492"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87875880","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 identification of relevant new information in clinical narrative","authors":"Rui Zhang, Serguei V. S. Pakhomov, G. Melton","doi":"10.1145/2110363.2110467","DOIUrl":"https://doi.org/10.1145/2110363.2110467","url":null,"abstract":"The ability to explore and visualize clinical information is important for clinicians when reviewing and cognitively synthesizing electronic clinical documents for new patients contained in electronic health record (EHR) systems. In this study, we explore the use of language models for detecting new and potentially relevant information within an individual patient's collection of clinical documents using an expert-based reference standard for evaluation. We achieved good accuracy with a heterogeneous system based on a modified n-gram language model with statistically-derived and classic stop word removal and lexical normalization, as well as heuristic rules. This technique also identified relevant new information not identified with the expert-derived reference standard. These methods appear promising for providing an automated means to improve the use of electronic documents by clinicians.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"23 3-4","pages":"837-842"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91489451","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}
Justin Martineau, R. Mokashi, David Chapman, M. Grasso, M. Brady, Y. Yesha, Y. Yesha, Antonio Cardone, A. Dima
{"title":"Sub-cellular feature detection and automated extraction of collocalized actin and myosin regions","authors":"Justin Martineau, R. Mokashi, David Chapman, M. Grasso, M. Brady, Y. Yesha, Y. Yesha, Antonio Cardone, A. Dima","doi":"10.1145/2110363.2110409","DOIUrl":"https://doi.org/10.1145/2110363.2110409","url":null,"abstract":"We describe a new distance-based metric to measure the strength of collocalization in multi-color microscopy images for user-selected regions. This metric helps to standardize, objectify, quantify, and even automate light microscopy observations. Our new algorithm uses this metric to automatically identify and annotate a donut shaped actomyosin stress fiber bundle evident in vascular smooth muscle cells on certain types of surfaces. Both the metric and the algorithm have been implemented as an open source plugin for the popular ImageJ toolkit. They are available for download at http://code.google.com/p/actin-myosin-plugin/. Using cells stained for the cytoskeletal proteins actin and myosin, we show how characteristics of the identified stress fiber bundle are indicative of the kind of surface the cell is placed upon, and prove that weak spots in this structure are correlated with local membrane extensions. Given the relationship between membrane extension, cell migration, vascular disease, embryonic development, and cancer metastasis we provide that these tools to enable biological research that could improve our quality of life.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"56 1","pages":"399-408"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88692186","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}
Ritu Khare, Yuan An, Jiexun Li, I. Song, Xiaohua Hu
{"title":"Exploiting semantic structure for mapping user-specified form terms to SNOMED CT concepts","authors":"Ritu Khare, Yuan An, Jiexun Li, I. Song, Xiaohua Hu","doi":"10.1145/2110363.2110397","DOIUrl":"https://doi.org/10.1145/2110363.2110397","url":null,"abstract":"The elements of clinical databases are usually named after the clinical terms used in various design artifacts. These terms are instinctively supplied by the users, and hence, different users often use different terms to describe the same clinical concept. This term diversity makes future database integration and analysis a huge challenge. In this paper, we study the problem of standardization of the terms used in a specific kind of user-designed artifact, the encounter forms or templates, using a popular clinical terminology, the SNOMED CT.\u0000 In particular, we focus on the problem of mapping the terms on an encounter form to SNOMED CT concepts. Existing term mapping techniques are solely based on syntactic string similarity. Such techniques are unable to disambiguate among the terms that resemble one another linguistically, and yet differ semantically. To improve existing techniques, we consider the context of a term in the mapping process and propose a hybrid approach relying on linguistics as well as structural information. For a given form term, this approach (i) exploits the semantic structure of the form to derive the term's context, and (ii) maps the term to a linguistically- matching SNOMED CT concept that is compatible with the derived context. We test the approach on over 900 clinician-specified terms used in 26 forms. This method achieves 23% improvement in precision and 38% improvement in recall, over a pure linguistic-based approach. Our first contribution is that we introduce and address a new problem of mapping form terms to standard concepts. The second contribution is that the experimental evaluation confirms that structural information has a major role in improving mapping performance, and in addressing the key challenges associated with semantic mapping.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"20 1","pages":"285-294"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89428806","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":"A spectral clustering technique for studying post-transplant kidney functions","authors":"A. Gangopadhyay, A. Joshi, R. Wali","doi":"10.1145/2110363.2110388","DOIUrl":"https://doi.org/10.1145/2110363.2110388","url":null,"abstract":"In this paper, we present a novel method for studying the deterioration of renal functions after kidney transplant. We track the kidney functions of 111 patients for 24 months after the kidney transplant and use the time series data to group the patients into four clusters. We have developed two graph-based algorithms for analyzing the data as a pre-processing step prior to the formation of the clusters. The resultant clusters thus formed are statistically analyzed to determine the socio-demographic and clinical factors that may provide insights into the renal functions after the transplants. We also compare the cluster formation against other manifold learning techniques. The quality of the clusters was assessed using the silhouette function. We discuss how our findings can be used for effective intervention strategies.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"10 1","pages":"201-208"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75062780","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":"Biomedical text mining for semantic search and knowledge discovery","authors":"S. Ananiadou","doi":"10.1145/2110363.2110365","DOIUrl":"https://doi.org/10.1145/2110363.2110365","url":null,"abstract":"Text mining based on semantic annotations is increasingly used to support semantic search and knowledge discovery in a number of biomedical applications. Recently, the extraction of complex events based on rich semantic metadata has been used for customized text mining applications such as query-answering systems, advanced searching, etc. Semantic annotations, named entities, facts, associations, events: all enrich document collections and facilitate knowledge discovery","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"70 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77892205","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}
Byron C. Wallace, Kevin Small, C. Brodley, J. Lau, T. Trikalinos
{"title":"Deploying an interactive machine learning system in an evidence-based practice center: abstrackr","authors":"Byron C. Wallace, Kevin Small, C. Brodley, J. Lau, T. Trikalinos","doi":"10.1145/2110363.2110464","DOIUrl":"https://doi.org/10.1145/2110363.2110464","url":null,"abstract":"Medical researchers looking for evidence pertinent to a specific clinical question must navigate an increasingly voluminous corpus of published literature. This data deluge has motivated the development of machine learning and data mining technologies to facilitate efficient biomedical research. Despite the obvious labor-saving potential of these technologies and the concomitant academic interest therein, however, adoption of machine learning techniques by medical researchers has been relatively sluggish. One explanation for this is that while many machine learning methods have been proposed and retrospectively evaluated, they are rarely (if ever) actually made accessible to the practitioners whom they would benefit. In this work, we describe the ongoing development of an end-to-end interactive machine learning system at the Tufts Evidence-based Practice Center. More specifically, we have developed abstrackr, an online tool for the task of citation screening for systematic reviews. This tool provides an interface to our machine learning methods. The main aim of this work is to provide a case study in deploying cutting-edge machine learning methods that will actually be used by experts in a clinical research setting.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"20 1","pages":"819-824"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78323242","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":"Medical equipment library design: revealing issues and best practice using DiCoT","authors":"Julia Werth, D. Furniss","doi":"10.1145/2110363.2110428","DOIUrl":"https://doi.org/10.1145/2110363.2110428","url":null,"abstract":"Medical Equipment Libraries (MELs) are a relatively new function for hospitals in the UK, which aim to save money and make medical practice safer. They centralize the management, maintenance and purchasing of medical equipment. They are being embraced and developed by some hospitals, and considered by others. Hence, there is a growing need to understand MEL practice and design. This paper compares three MELs through interviews and observations of everyday practice using DiCoT (Distributed Cognition for Teamwork) as a method for multisite comparison. This is a novel use of the method that reveals general issues and best practices across contexts. Our results complement the little formal information that is available on MELs, and explores the workings of the library as a socio-technical system. As far as we are aware no empirical studies have been published in this area. We conclude with design opportunities and requirements for MELs, and propose DiCoT as an effective way to compare socio-technical systems, including revealing issues and best practices in other clinical contexts more broadly.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"103 1","pages":"583-592"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74275063","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}
A. Lahane, Y. Yesha, M. Grasso, A. Joshi, A. Park, Jimmy Lo
{"title":"Detection of unsafe action from laparoscopic cholecystectomy video","authors":"A. Lahane, Y. Yesha, M. Grasso, A. Joshi, A. Park, Jimmy Lo","doi":"10.1145/2110363.2110400","DOIUrl":"https://doi.org/10.1145/2110363.2110400","url":null,"abstract":"Wellness and healthcare are central to the lives of all people, young or old, healthy or ill, rich or poor. New computing and behavioral research can lead to transformative changes in the cost-effective delivery of quality and personalized healthcare. Also beyond the daily practice of healthcare and wellbeing, basic information technology research can provide the foundations for new directions in the clinical sciences via tools and analyses that identify subtle but important causal signals in the fusing of clinical, behavioral, environmental and genetic data. In this paper we describe a system that analyzes images from the laparoscopic videos. It indicates the possibility of an injury to the cystic artery by automatically detecting the proximity of the surgical instruments with respect to the cystic artery. The system uses machine learning algorithm to classify images and warn surgeons against probable unsafe actions.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"37 1","pages":"315-322"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74858741","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}
Xiangyu Fan, Javed Mostafa, K. Mane, Cassidy R. Sugimoto
{"title":"Personalization is not a panacea: balancing serendipity and personalization in medical news content delivery","authors":"Xiangyu Fan, Javed Mostafa, K. Mane, Cassidy R. Sugimoto","doi":"10.1145/2110363.2110445","DOIUrl":"https://doi.org/10.1145/2110363.2110445","url":null,"abstract":"Personalization is viewed as a potential solution to the \"information overload\" problem. In contrast, serendipity is a natural part of human information seeking process that can lead to unexpected and useful discoveries. It appears both serendipity and personalization are important. However, it remains unclear how these modes of interaction impact content retrieval and consumption. To empirically analyze the influence of personalization and serendipity on information retrieval, a medical news information system named MedSIFTER was developed. The system can personalize the presentation of news articles based on users' interest profiles. Using a control variable, built into the system, MeSIFTER's personalization level can be modulated, ranging from high to low (or zero). In this study, based on MedlinePlus as main information source, three different system modalities were compared (zero, low, and high levels of personalization). The experimental analysis engaged three different user groups, over a four week period. Strong evidence of serendipity was found across all three user groups, independent of the level of personalization. Users also appeared to be uniformly satisfied regardless of the level of personalization.","PeriodicalId":90523,"journal":{"name":"IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium","volume":"31 1","pages":"709-714"},"PeriodicalIF":0.0,"publicationDate":"2012-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84217264","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}