The number of citations that a research paper receives can be used as a measure of its scientific impact. The objective of this study was to identify and to examine the characteristics of top 100 cited articles in the field of Medical Informatics based on data acquired from the Thomson Reuters' Web of Science (WOS) in October, 2016. The data was collected using two procedures: first we included articles published in the 24 journals listed in the "Medical Informatics" category; second, we retrieved articles using the key words: "informatics", "medical informatics", "biomedical informatics", "clinical informatics" and "health informatics". After removing duplicate records, articles were ranked by the number of citations they received. When the 100 top cited articles had been identified, we collected the following information for each record: all WOS database citations, year of publication, journal, author names, authors' affiliation, country of origin and topics indexed for each record. Citations for the top 100 articles ranged from 346 to 7875, and citations per year ranged from 11.12 to 525. The majority of articles were published in the 2000s (n=43) and 1990s (n=38). Articles were published across 10 journals, most commonly Statistics in medicine (n=71) and Medical decision making (n=28). The articles had an average of 2.47 authors. Statistics and biostatistics modeling was the most common topic (n=71), followed by artificial intelligence (n=12), and medical errors (n=3), other topics included data mining, diagnosis, bioinformatics, information retrieval, and medical imaging. Our bibliometric analysis illustrated a historical perspective on the progress of scientific research on Medical Informatics. Moreover, the findings of the current study provide an insight on the frequency of citations for top cited articles published in Medical Informatics as well as quality of the works, journals, and the trends steering Medical Informatics.

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Purpose -Medicine is heavily dependent on images and health care professionals use medical images for clinical, educational and research purposes. This paper aims to investigate the resources used by health care professionals while searching for medical images. Design/methodology/approach -The research is based on a qualitative study that uses the Straussian version of grounded theory and involved 29 health care professionals from various health and biomedical departments working within Sheffield Teaching Hospitals NHS (National Health Service) Foundation Trust. Data collection was carried out using semi-structured interviews and think-aloud protocols. Findings -The findings show that health care professionals seek medical images in a variety of visual information sources, including those found online and from published medical literature. The research also identified a number of difficulties that health care professionals face when searching for medical images in various image resources. Originality/value -There have been few studies that investigated the image resources used by health care professionals. Thus, this study contributes to the understanding of medical image resources and information needs of health care professionals. A clear understanding of the medical image information needs of health care professionals is also vital to the design process and development of medical image retrieval systems.

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This article explores the models and frameworks developed on “research impact’. We aim to provide a comprehensive overview of related literature through scoping study method. The present research investigates the nature, objectives, approaches, and other main attributes of the research impact models. It examines to analyze and classify models based on their characteristics. Forty-seven studies and 10 reviews published between 1996 and 2020 were included in the analysis. The majority of models were developed for the impact assessment and evaluation purposes. We identified three approaches in the models, namely outcome-based, process-based, and those utilized both of them, among which the outcome-based approach was the most frequently used by impact models and evaluation was considered as the main objective of this group. The process-based ones were mainly adapted from the W.K. Kellogg Foundation logic model and were potentially eligible for impact improvement. We highlighted the scope of processes and other specific features for the recent models. Given the benefits of the process-based approach in enhancing and accelerating the research impact, it is important to consider such approach in the development of impact models. Effective interaction between researchers and stakeholders, knowledge translation, and evidence synthesis are the other possible driving forces contributing to achieve and improve impact.