Evaluating Consensus Among Physicians in Medical Knowledge Base Construction

1993 ◽  
Vol 32 (02) ◽  
pp. 137-145 ◽  
Author(s):  
D. A. Giuse ◽  
R. A. MMer ◽  
R. A. Bankowitz ◽  
J. E. Janosky ◽  
F. Davidoff ◽  
...  
Keyword(s):  
Reference Material ◽  
Knowledge Base ◽  
Medical Literature ◽  
Medical Knowledge ◽  
Supporting Evidence ◽  
Perinephric Abscess ◽  
Knowledge Base Construction ◽  
Selection Of ◽  
Extract Information ◽  
Author Knowledge

Abstract:This study evaluates inter-author variability in knowledge base construction. Seven board-certified internists independently profiled “acute perinephric abscess”, using as reference material a set of 109 peer-reviewed articles. Each participant created a list of findings associated with the disease, estimated the predictive value and sensitivity of each finding, and assessed the pertinence of each article for making each judgment. Agreement in finding selection was significantly different from chance: seven, six, and five participants selected the same finding 78.6, 9.8, and 1.6 times more often than predicted by chance. Findings with the highest sensitivity were most likely to be included by all participants. The selection of supporting evidence from the medical literature was significantly related to each physician’s agreement with the majority. The study shows that, with appropriate guidance, physicians can reproducibly extract information from the medical literature, and thus established a foundation for multi-author knowledge base construction.

Drug Repurposing for Parkinson’s Disease by Integrating Knowledge Graph Completion Model and Knowledge Fusion of Medical Literature

2021 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Xiaolin Zhang ◽  
Chao Che
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Knowledge Base ◽  
Medical Literature ◽  
Medical Knowledge ◽  
Drug Repurposing ◽  
New Drugs ◽  
Knowledge Graph ◽  
Knowledge Fusion ◽  
Effective Drugs

The prevalence of Parkinson’s disease increases a tremendous medical and economic burden to society. Therefore, the effective drugs are urgently required. However, the traditional development of effective drugs is costly and risky. Drug repurposing, which identifies new applications for existing drugs, is a feasible strategy for discovering new drugs for Parkinson’s disease. Drug repurposing is based on sufficient medical knowledge. The local medical knowledge base with manually labeled data contains a large number of accurate, but not novel, medical knowledge, while the medical literature containing the latest knowledge is difficult to utilize, because of unstructured data. This paper proposes a framework, named Drug Repurposing for Parkinson’s disease by integrating Knowledge Graph Completion method and Knowledge Fusion of medical literature data (DRKF) in order to make full use of a local medical knowledge base containing accurate knowledge and medical literature with novel knowledge. DRKF first extracts the relations that are related to Parkinson’s disease from medical literature and builds a medical literature knowledge graph. After that, the literature knowledge graph is fused with a local medical knowledge base that integrates several specific medical knowledge sources in order to construct a fused medical knowledge graph. Subsequently, knowledge graph completion methods are leveraged to predict the drug candidates for Parkinson’s disease by using the fused knowledge graph. Finally, we employ classic machine learning methods to repurpose the drug for Parkinson’s disease and compare the results with the method only using the literature-based knowledge graph in order to confirm the effectiveness of knowledge fusion. The experiment results demonstrate that our framework can achieve competitive performance, which confirms the effectiveness of our proposed DRKF for drug repurposing against Parkinson’s disease. It could be a supplement to traditional drug discovery methods.

Consistency enforcement in medical knowledge base construction

1993 ◽  
Vol 5 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Dario A. Giuse ◽  
Nunzia B. Giuse ◽  
Randolph A. Miller
Keyword(s):  
Knowledge Base ◽  
Medical Knowledge ◽  
Knowledge Base Construction

Medical Literature Searches -How Many Bibliographic Databases are Needed for Sufficient Retrieval in Medical Topics?

1985 ◽  
Vol 24 (03) ◽  
pp. 163-165 ◽  
Author(s):  
K. John
Keyword(s):  
Medical Literature ◽  
Cost Effective ◽  
Medical Faculty ◽  
Bibliographic Databases ◽  
Literature Searches ◽  
Selection Of

SummaryAs many bibliographic services in medicine are offered, literature searches in eight databases at DIMDI were performed to find out which database is most important in medicine. The distribution of publications from members of the medical faculty of Frankfurt University was examined. No save prediction is possible as to which database will yield most articles. Overlapping from different databases is often rather low. The selection of an appropriate database mix for sufficient recall and in a cost-effective manner.is a task for an experienced searcher.

scholarly journals Cinnabar, Calomel and the Art of kushtasāzī: Mercurial Preparations in Unani Medicine

2015 ◽  
Vol 69 (4) ◽  
pp. 901-932 ◽  
Author(s):  
Claudia Preckel
Keyword(s):  
South Asia ◽  
Fifteenth Century ◽  
Medical Literature ◽  
Ancient Greece ◽  
Unani Medicine ◽  
Islamic Medicine ◽  
Selection Of

Abstract This paper examines the role of mercury in “Graeco-Islamic” medicine, which is referred to as Ṭibb-e yūnānī or unani medicine in South Asia. Having its origin in Ancient Greece, unani medicine spread to the Arabic countries and from the fifteenth century onwards to India. With its main roots in the Greek and Latin sources, the most influential works of ‘ilm al-adviya (pharmacology) were translated into Arabic, Persian and Urdu. Mercury (Arabic: zībaq; Persian: sīmāb; Urdu: sīmāb and pāra) played an important role in all Indian traditions of medicine, and had a prominent place in unani medicine. This paper highlights the historical use of mercury in Indian, Persian and Urdu medical literature, the discourses on its efficacy and some of the important mercurial preparations presented in a selection of unani works. Further, the use of mercury as a single and compound drug and its role in the treatment of different diseases will be analysed.

scholarly journals Taxonomy Extraction for Customer Service Knowledge Base Construction

2019 ◽  
pp. 175-190
Author(s):  
Bianca Pereira ◽  
Cecile Robin ◽  
Tobias Daudert ◽  
John P. McCrae ◽  
Pranab Mohanty ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Customer Service ◽  
Knowledge Base Construction

‘Female Nectar’: A Study of Hybridity and Gender in Contemporary Tibetan Medical Literature on Menstruation

2012 ◽  
Vol 6 (2) ◽  
pp. 387-420 ◽  
Author(s):  
Jenny Bright
Keyword(s):  
Medical Literature ◽  
Medical Knowledge ◽  
Tibetan Medicine ◽  
Biomedical Knowledge ◽  
Women And Gender ◽  
Cultural Perceptions ◽  
And Gender ◽  
Key Aspects ◽  
Medical Writers

Abstract This essay examines contemporary Tibetan medical literature that deals with menstruation, focusing on the relations among medical, religious and cultural perceptions of women and gender. Present-day medical writers present a hybrid account of menstruation, incorporating key aspects of Tibetan medicine, such as the refining processes of digestion and the red element, with biomedical knowledge, notably the role of hormones. The integration of biomedical thought by Tibetan writers works to substantiate and bolster the validity of Tibetan medical claims, rather than discredit them. Consequently, contemporary writers are able to articulate medical knowledge about women that is as much about Tibetan religious and cultural perceptions of gender and sexed-bodies, as it is ‘scientific’.

Computer Service Support at Glenview Hospital

2011 ◽  
pp. 387-400
Author(s):  
Martha Garcia-Murillo ◽  
Paula Maxwell ◽  
Simon Boyce ◽  
Raymond St. Denis ◽  
William Bistline
Keyword(s):  
Knowledge Base ◽  
Data Entry ◽  
Computer Users ◽  
Help Desk ◽  
Staff Members ◽  
Service Support ◽  
Self Help ◽  
Information Center ◽  
The Web ◽  
Selection Of

This case focuses on the challenges of managing a help desk that supports computer users. There are two main technologies that the Information Center (IC) uses to provide this service: the call distributing system and the knowledge base, which is also available on the Web. The choice of technologies affected the service provided by the help desk staff. Specifically, the call distributing system was unable to provide enough information regarding the number of calls answered, dropped, and allocated among the different staff members. The hospital knowledge base, on the other hand, is created based on peoples documentation of the problem and selection of keywords, which has led to inconsistencies in the data entry. One of the management challenges for the Information Center is to foster self-help and minimize the number of requests to the IC staff. This case presents the difficulties and some of the initiatives that the IC has considered to solve these problems.

Mining information from sentences through Semantic Web data and Information Extraction tasks

2020 ◽  
pp. 016555152093438
Author(s):  
Jose L. Martinez-Rodriguez ◽  
Ivan Lopez-Arevalo ◽  
Ana B. Rios-Alvarado
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Information Extraction ◽  
Knowledge Base ◽  
Semantic Similarity ◽  
Similarity Measure ◽  
Real World ◽  
Semantic Similarity Measure ◽  
Web Standards ◽  
Extract Information

The Semantic Web provides guidelines for the representation of information about real-world objects (entities) and their relations (properties). This is helpful for the dissemination and consumption of information by people and applications. However, the information is mainly contained within natural language sentences, which do not have a structure or linguistic descriptions ready to be directly processed by computers. Thus, the challenge is to identify and extract the elements of information that can be represented. Hence, this article presents a strategy to extract information from sentences and its representation with Semantic Web standards. Our strategy involves Information Extraction tasks and a hybrid semantic similarity measure to get entities and relations that are later associated with individuals and properties from a Knowledge Base to create RDF triples (Subject–Predicate–Object structures). The experiments demonstrate the feasibility of our method and that it outperforms the accuracy provided by a pattern-based method from the literature.

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