Automatic text processing
Talking Work: Language-games, Organisations and Computer Supported Cooperative Work
Computer Supported Cooperative Work
Exploring the use of concept spaces to improve medical information retrieval
Decision Support Systems
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Guiding the User: An Ontology Driven Interface
UIDIS '99 Proceedings of the 1999 User Interfaces to Data Intensive Systems
On-line trust: concepts, evolving themes, a model
International Journal of Human-Computer Studies - Special issue: Trust and technology
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Supporting informality: team working and integrated care records
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
IEEE Transactions on Knowledge and Data Engineering
Analyzing the semantics of patient data to rank records of literature retrieval
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
Usage patterns of collaborative tagging systems
Journal of Information Science
Investigating interactions of trust and interest similarity
Decision Support Systems
MedicoPort: A medical search engine for all
Computer Methods and Programs in Biomedicine
A survey of trust in computer science and the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Redesigning electronic health record systems to support public health
Journal of Biomedical Informatics
Collaborative information seeking: A field study of a multidisciplinary patient care team
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
An ontological knowledge framework for adaptive medical workflow
Journal of Biomedical Informatics
TREPPS: A Trust-based Recommender System for Peer Production Services
Expert Systems with Applications: An International Journal
Q-rater: A collaborative reputation system based on source credibility theory
Expert Systems with Applications: An International Journal
Multidimensional credibility model for neighbor selection in collaborative recommendation
Expert Systems with Applications: An International Journal
Fuzzy computational models for trust and reputation systems
Electronic Commerce Research and Applications
Medical knowledge management for specific hospital departments
Expert Systems with Applications: An International Journal
Personalization of tagging systems
Information Processing and Management: an International Journal
Understanding together: sensemaking in collaborative information seeking
Proceedings of the 2010 ACM conference on Computer supported cooperative work
International Journal of Human-Computer Studies
A recommender system based on tag and time information for social tagging systems
Expert Systems with Applications: An International Journal
An ontology-based comparative anatomy information system
Artificial Intelligence in Medicine
Context-aware recommendation using rough set model and collaborative filtering
Artificial Intelligence Review
Collaborative user modeling with user-generated tags for social recommender systems
Expert Systems with Applications: An International Journal
Trust estimation in a virtual team: A decision support method
Expert Systems with Applications: An International Journal
Antecedents of application service continuance: A synthesis of satisfaction and trust
Expert Systems with Applications: An International Journal
A semantic graph-based approach to biomedical summarisation
Artificial Intelligence in Medicine
Trust Modeling for Networked Organizations Using Reputation and Collaboration Estimates
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text
Artificial Intelligence in Medicine
A framework for collaborative filtering recommender systems
Expert Systems with Applications: An International Journal
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Purpose: Clinicians rely on a large amount of medical knowledge when performing clinical work. In clinical environment, clinical organizations must exploit effective methods of seeking and recommending appropriate medical knowledge in order to help clinicians perform their work. Method: Aiming at supporting medical knowledge search more accurately and realistically, this paper proposes a collaboration-based medical knowledge recommendation approach. In particular, the proposed approach generates clinician trust profile based on the measure of trust factors implicitly from clinicians' past rating behaviors on knowledge items. And then the generated clinician trust profile is incorporated into collaborative filtering techniques to improve the quality of medical knowledge recommendation, to solve the information-overload problem by suggesting knowledge items of interest to clinicians. Results: Two case studies are conducted at Zhejiang Huzhou Central Hospital of China. One case study is about the drug recommendation hold in the endocrinology department of the hospital. The experimental dataset records 16 clinicians' drug prescribing tracks in six months. This case study shows a proof-of-concept of the proposed approach. The other case study addresses the problem of radiological computed tomography (CT)-scan report recommendation. In particular, 30 pieces of CT-scan examinational reports about cerebral hemorrhage patients are collected from electronic medical record systems of the hospital, and are evaluated and rated by 19 radiologists of the radiology department and 7 clinicians of the neurology department, respectively. This case study provides some confidence the proposed approach will scale up. Conclusion: The experimental results show that the proposed approach performs well in recommending medical knowledge items of interest to clinicians, which indicates that the proposed approach is feasible in clinical practice.