scholarly journals UMLS at 30 years, how is it used and published?---A systematic review (Preprint)

2020 ◽  
Author(s):  
Xia Jing
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Data Mining ◽  
Medical Education ◽  
Information Retrieval ◽  
Patient Care ◽  
Knowledge Discovery ◽  
Digital Library ◽  
Digital Libraries ◽  
English Language

BACKGROUND Background: The unified medical language system (UMLS) has been a critical tool in biomedical and health informatics, and the year 2020 marks the 30th anniversary of UMLS. Despite its longevity, there is no systematic review on UMLS, in general. Thus, this systematic review was conducted to provide an overview of UMLS and its usage in English-language publications in the last 30 years. OBJECTIVE Objectives: The objective is twofold: to provide a comprehensive and systematic picture of the themes, their subtopics, and the publications under each category and to document systematic evidence of UMLS and how it has been used in English-language publications in the last 30 years. METHODS Methods: PubMed, ACM Digital Library, and Nursing & Allied Health Database were used to search for literature. The primary literature search strategy was as follows: UMLS was used as a MeSH term or a keyword or appeared in the title or abstract. Only English-language publications were considered. RESULTS Results: A total of 943 publications were included in the final analysis. After analysis and categorization of publications, UMLS was found to be used in the following emerging themes: natural language processing (NLP) (230 publications), information retrieval (125 publications), terminology study (90 publications), ontology and modeling (80 publications), medical subdomains (76 publications), other language studies (53 publications), artificial intelligence tools and applications (46 publications), patient care (35 publications), data mining and knowledge discovery (25 publications), medical education (20 publications), degree-related theses (13 publications), and digital library (5 publications) as well as UMLS itself (150 publications). CONCLUSIONS Conclusions: UMLS has been used and published successfully in patient care, medical education, digital libraries, and software development, as originally planned, as well as in degree-related theses, building artificial intelligence tools, data mining and knowledge discovery and more foundational work in methodology and middle layers that may lead to advanced products. NLP, UMLS itself, and information retrieval are the three themes with the most publications. The review provides systematic evidence of UMLS in English-language peer-reviewed publications in the last 30 years.

Information Analysis in Digital Library Environments

2013 ◽  
pp. 87-92
Author(s):  
Lauren Harrison
Keyword(s):  
Information Retrieval ◽  
Text Mining ◽  
Knowledge Discovery ◽  
Digital Library ◽  
Digital Libraries ◽  
Semantic Content ◽  
Direct Access ◽  
Pipeline Pilot ◽  
Analysis Of Results ◽  
Mining Tools

This chapter addresses the question of how the analysis of results retrieved from online bibliographic information systems changed over the last 32 years as digital libraries have evolved. It demonstrates that Digital Libraries of the future will enable knowledge discovery by providing direct access to the semantic content of documents through the implementation of text mining tools. To achieve this research with IR systems and text-mining tools, pipeline pilot (Bandy, et al., 2009), I2E (Vellay, 2009), and BioText will need to be conducted by experts in information retrieval not just subject scientific specialists.

scholarly journals Morning Report: Can an Established Medical Education Tradition Be Validated?

2013 ◽  
Vol 5 (3) ◽  
pp. 374-384 ◽  
Author(s):  
Matthew McNeill ◽  
Sayed K. Ali ◽  
Daniel E. Banks ◽  
Ishak A. Mansi
Keyword(s):  
Medical Education ◽  
Patient Care ◽  
Outcome Measures ◽  
English Language ◽  
Meta Analysis ◽  
The United States ◽  
Cochrane Library ◽  
Clinical Effects ◽  
Morning Report ◽  
Residency Programs

Abstract Background Morning report is accepted as an essential component of residency education throughout different parts of the world. Objective To review the evidence of the educational value, purpose, methods, and outcomes of morning report. Methods A literature search of PubMed, Ovid, and the Cochrane Library for English-language studies published between January 1, 1966, and October 31, 2011, was performed. We searched for keywords and Medical Subject Heading terms related to medical education, methods, attitudes, and outcomes in regard to “morning report.” Title and abstract review, followed by a full-text review by 3 authors, was performed to identify all pertinent articles. Results We identified 71 citations; 40 articles were original studies and 31 were commentaries, editorials, or review articles; 56 studies (79%) originated from internal medicine residency programs; 6 studies (8%) focused on ambulatory morning report; and 63 (89%) originated from the United States. Identified studies varied in objectives, methods, and outcome measures, and were not suitable for meta-analysis. Main outcome measures were resident satisfaction, faculty satisfaction, preparation for professional examinations, use of evidence-based medicine, clinical effects on patient care, adverse event detection, and utilization of a curriculum in case selection. Conclusions Morning report has heterogeneous purposes, methods, and settings. As an educational tool, morning report is challenging to define, its outcome is difficult to measure, and this precludes firm conclusions about its contribution to resident education or patient care. Residency programs should tailor morning report to meet their own unique educational objectives and needs.

Cross-Lingual Information Retrieval

2005 ◽  
pp. 153-170 ◽  
Author(s):  
Christopher Yang ◽  
Kar W. Li
Keyword(s):  
Information Retrieval ◽  
Digital Library ◽  
Digital Libraries ◽  
World Wide ◽  
Relevant Information ◽  
Semantic Interoperability ◽  
Library Research ◽  
The World ◽  
Cross Lingual ◽  
Multiple Languages

Structural and semantic interoperability have been the focus of digital library research in the early 1990s. Many research works have been done on searching and retrieving objects across variations in protocols, formats, and disciplines. As the World Wide Web has become more popular in the last ten years, information is available in multiple languages in global digital libraries. Users are searching across the language boundary to identify the relevant information that may not be available in their own language. Cross-lingual semantic interoperability has become one of the focuses in digital library research in the late 1990s. In particular, research in cross-lingual information retrieval (CLIR) has been very active in recent conferences on information retrieval, digital libraries, knowledge management, and information systems. The major problem in CLIR is how to build the bridge between the representations of user queries and documents if they are of different languages.

Metadata and Metaphors in Visual Interfaces to Digital Libraries

2009 ◽  
pp. 270-277
Author(s):  
Ali Shiri
Keyword(s):  
Information Retrieval ◽  
Digital Library ◽  
User Interfaces ◽  
Digital Libraries ◽  
Information Search ◽  
Interface Design ◽  
Visual Metaphors ◽  
Key Variables ◽  
Design Ideas ◽  
Visual Interfaces

This chapter introduces a new category of digital library user interfaces called metadata-enhanced visual interfaces. Drawing on the earlier information retrieval visual interfaces that have made use of thesauri, this chapter will review and analyze metadata-enhanced visual interfaces to digital libraries based on two key variables, namely metadata elements used for visualization purposes and visual metaphors incorporated into the user interfaces. The aim of this study is to inform the design of visual interfaces for digital libraries through bringing together issues that have roots in such communities as information retrieval, digital libraries, human-computer interaction, and metadata. The findings of this study provide design ideas and implications for digital library interface design in terms of the various metadata-based information search and retrieval features for visualization purposes.

scholarly journals Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Naseer Ahmed ◽  
Maria Shakoor Abbasi ◽  
Filza Zuberi ◽  
Warisha Qamar ◽  
Mohamad Syahrizal Bin Halim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Full Text ◽  
Patient Management ◽  
English Language ◽  
Clinical Performance ◽  
Research Question ◽  
Time Saving ◽  
Artificial Intelligence Techniques ◽  
Clinical Scenarios

Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

scholarly journals Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic Review

Children ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 93
Author(s):  
Lorenzo Desideri ◽  
Patricia Pérez-Fuster ◽  
Gerardo Herrera
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Information And Communication Technologies ◽  
Digital Libraries ◽  
English Language ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Screening Tools ◽  
Early Screening

The aim of this systematic review is to identify recent digital technologies used to detect early signs of autism spectrum disorder (ASD) in preschool children (i.e., up to six years of age). A systematic literature search was performed for English language articles and conference papers indexed in Pubmed, PsycInfo, ERIC, CINAHL, WoS, IEEE, and ACM digital libraries up until January 2020. A follow-up search was conducted to cover the literature published until December 2020 for the usefulness and interest in this area of research during the Covid-19 emergency. In total, 2427 articles were initially retrieved from databases search. Additional 481 articles were retrieved from follow-up search. Finally, 28 articles met the inclusion criteria and were included in the review. The studies included involved four main interface modalities: Natural User Interface (e.g., eye trackers), PC or mobile, Wearable, and Robotics. Most of the papers included (n = 20) involved the use of Level 1 screening tools. Notwithstanding the variability of the solutions identified, psychometric information points to considering available technologies as promising supports in clinical practice to detect early sign of ASD in young children. Further research is needed to understand the acceptability and increase use rates of technology-based screenings in clinical settings.

scholarly journals A Systematic Review of Patient-Facing Visualizations of Personal Health Data

2019 ◽  
Vol 10 (04) ◽  
pp. 751-770
Author(s):  
Meghan Reading Turchioe ◽  
Annie Myers ◽  
Samuel Isaac ◽  
Dawon Baik ◽  
Lisa V. Grossman ◽  
...  
Keyword(s):  
Systematic Review ◽  
Digital Library ◽  
Data Science ◽  
English Language ◽  
Health Data ◽  
Personal Health ◽  
Line Graphs ◽  
Data Types ◽  
Effective Manner ◽  
Number Lines

Abstract Objectives As personal health data are being returned to patients with increasing frequency and volume, visualizations are garnering excitement for their potential to facilitate patient interpretation. Evaluating these visualizations is important to ensure that patients are able to understand and, when appropriate, act upon health data in a safe and effective manner. The objective of this systematic review was to review and evaluate the state of the science of patient-facing visualizations of personal health data. Methods We searched five scholarly databases (PubMed, Embase, Scopus, ACM Digital Library [Association for Computing Machinery Digital Library], and IEEE Computational Index [Institute of Electrical and Electronics Engineers Computational Index]) through December 1, 2018 for relevant articles. We included English-language articles that developed or tested one or more patient-facing visualizations for personal health data. Three reviewers independently assessed quality of included articles using the Mixed methods Appraisal Tool. Characteristics of included articles and visualizations were extracted and synthesized. Results In 39 articles included in the review, there was heterogeneity in the sample sizes and methods for evaluation but not sample demographics. Few articles measured health literacy, numeracy, or graph literacy. Line graphs were the most common visualization, especially for longitudinal data, but number lines were used more frequently in included articles over past 5 years. Article findings suggested more patients understand the number lines and bar graphs compared with line graphs, and that color is effective at communicating risk, improving comprehension, and increasing confidence in interpretation. Conclusion In this review, we summarize types and components of patient-facing visualizations and methodologies for development and evaluation in the reviewed articles. We also identify recommendations for future work relating to collecting and reporting data, examining clinically actionable boundaries for diverse data types, and leveraging data science. This work will be critically important as patient access of their personal health data through portals and mobile devices continues to rise.

scholarly journals EDUCATING MEDICAL PRACTITIONERS ABOUT MEDICAL BILLING: A SYSTEMATIC REVIEW OF THE LITERATURE

2021 ◽  
Author(s):  
Margaret Faux ◽  
Jon Adams ◽  
Jon Wardle
Keyword(s):  
Systematic Review ◽  
Medical Education ◽  
Health Systems ◽  
English Language ◽  
Grey Literature ◽  
Health Financing ◽  
Review Of The Literature ◽  
Medical Practitioners ◽  
Education Needs ◽  
Medical Billing

ABSTRACTIntroductionThe WHO has suggested the solution to leakage in health systems caused by waste, corruption and fraud is policing and prosecution. However, a growing body of evidence suggests leakage may not always be fraudulent or corrupt, with researchers suggesting medical practitioners may sometimes struggle to understand increasingly complex legal requirements around health financing and billing transactions, which may be improved through education. To explore this phenomenon further, we undertook a systematic review of the literature to identify the medical billing education needs of medical practitioners and whether those needs are being met.MethodsEligible records included English language materials published between 1 January 2000 and 4 May 2020, including empirical research, commentary, opinions and grey literature.ResultsWe identified 74 records as directly relevant to the search criteria. Despite a comprehensive international search, studies were limited to three countries (Australia, Canada, U.S), indicating a need for further work internationally. The literature suggests the education needs of medical practitioners in relation to medical billing compliance are not being met and medical practitioners desire more education on this topic. Evidence suggests education may be effective in improving medical billing compliance and reducing waste in health systems and there is broad agreement amongst medical education stakeholders in multiple jurisdictions that medical billing should be viewed as a core competency of medical education, though there is an apparent inertia to act. Penalties for non-compliant medical billing are serious and medical practitioners are at risk of random audits and investigations for breaches of sometimes incomprehensible, and highly interpretive regulations they may never have been taught.ConclusionDespite acknowledged significance of leakage in health systems due to poor practitioner knowledge of billing practices, there has been very little research to date on education interventions to improve health system efficiency at a practitioner level.

scholarly journals Analisis Potensi Asal Sekolah pada Jalur Penerimaan Mahasiswa Baru di Universitas Lampung menggunakan Algoritma K-Means

Electrician ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 7
Author(s):  
Wulan Rahma Izzati ◽  
Muhamad Komarudin ◽  
Hery Dian Septama ◽  
Yessi Mulyani
Keyword(s):  
Data Mining ◽  
Medical Education ◽  
English Language ◽  
Language Education ◽  
Software Tools ◽  
State Universities ◽  
English Language Education ◽  
Study Program ◽  
Calculation Results ◽  
New Students

Intisari — Permenristekdikti nomor 126 tahun 2016 mengatur Penerimaan Mahasiswa Baru Program Sarjana pada Perguruan Tinggi Negeri, yakni Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN), Seleksi Bersama Masuk Perguruan Tinggi Negeri (SBMPTN), dan Seleksi Mandiri. Di Universitas Lampung (UNILA), asal sekolah calon pendaftar dijadikan salah satu parameter untuk diterimanya calon mahasiswa baru dengan melihat potensi unggul dibidangnya dari setiap sekolah per tahunnya. Pada jalur SNMPTN dan SBMPTN di UNILA akan dilakukan analisis data dengan menggunakan software tools rapidminer serta menerapkan teknik data mining Algoritma K-means untuk melihat potensi serta konsistensi nilai diberbagai asal sekolah pada setiap tahunnya. Dari hasil perhitungan menggunakan Algotitma K- means diketahui jalur SBMPTN pada jenis ujian SAINTEK, SOSHUM dan IPC didominasi asal sekolah Bandar Lampung dibagi menjadi 3 kelas dimana claster_ 0 (program studi Agroteknologi 31%), claster_1 (program studi Teknik Sipil 37%), dan claster_2 (Pendidikam Kedokteran 95). Pada jalur SBMPTN dengan jenis ujian SOSHUM terdiri dari claster_0 (program studi Hukum 48%), claster_1 (program studi Manajemen 44%), dan claster_2 (program studi Akuntansi 47%). Pada jenis ujian Campuran terdiri dari claster_0 (program studi Hukum sebesar 50%), claster_1 (program studi Pendidikan Bahasa Inggris 23%), dan claster_2 (program studi Akuntansi 38%) selama lima tahun terakhir. Pada jalur penerimaan SNMPTN, claster_0 (Hukum 58%), dan claster_1 (Hukum 37%) didominasi oleh asal sekolah Bandar Lampung, sedangkan pada claster_2 (Pendidikan Kedokteran 46%) didominasi oleh asal sekolah kabupaten Lampung Barat selama empat tahun terakhir.Kata kunci — data mining, k-means, penerimaan mahasiswa baru, SBMPTN, SNMPTN Abstract — Permenristekdikti number 126 of 2016 regulates the New Student Admission for Undergraduate Program at State Universities, namely SNMPTN, SBMPTN, and Independent Selection. University of Lampung (UNILA), makes the origin of prospective applicants' schools as one of the parameters for the acceptance of prospective new students by seeing the superior potential in their fields from each school per year. The pattern of potential values based on origin school has not been analyzed in detail for the SNMPTN and SBMPTN pathways at UNILA. Data analysis will be performed using rapidminer software tools and applying K-means Algorithm data mining techniques to see the potential and consistency of values in various origin schools each year. From the calculation results using the K-means Algorithm it is known that the SBMPTN pathway in the SAINTEK, SOSHUM and IPC. dominated by the origin of Bandar Lampung schools divided into 3 classes where claster_0 (Agrotechnology study program 31%), claster_1 (Civil Engineering study program 37%), and claster_2 (Medical Education 95 48%), claster_1 (Management study program 44%), and claster_2 (Accounting study program 47%) .The types of Mixed examinations consist of claster_0 (Law study program by 50%), claster_1 (English Language Education program 23%), and claster_2 (Accounting study program 38%) for the last five years, on the admission path of SNMPTN, claster_0 (Law 58%), and claster_1 (Law 37%) dominated by the origin of Bandar Lampung schools, while in claster_2 (Medical Education 46%) dominated by the origin of the West Lampung district school for the past four years.Keywords— data mining, k-means, acceptance of new students, SBMPTN, SNMPTN

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