Medical Imaging Informatics and Medical Informatics: Opportunities and Constraints

Toward a formalization of the process to select IMIA Yearbook best papers

BACKGROUND

Each year, the International Medical Informatics Association Yearbook recognizes significant scientific papers, labelled as "best papers", published the previous year in the subfields of biomedical informatics that correspond to the different section topics of the journal. For each section, about fifteen pre-selected "candidate" best papers are externally peer-reviewed to select the actual best papers. Although based on the available literature, little is known about the pre-selection process.

OBJECTIVE

To move toward an explicit formalization of the candidate best papers selection process to reduce variability in the literature search across sections and over years.

METHODS

A methodological framework is proposed to build for each section topic specific queries tailored to PubMed and Web of Science citation databases. The two sets of returned papers are merged and reviewed by two independent section editors and citations are tagged as "discarded", "pending", and "kept". A protocolized consolidation step is then jointly conducted to resolve conflicts. A bibliographic software tool, BibReview, was developed to support the whole process.

RESULTS

The proposed search strategy was fully applied to the Decision Support section of the 2013 edition of the Yearbook. For this section, 1124 references were returned (689 PubMed-specific, 254 WoS-specific, 181 common to both databases) among which the 15 candidate best papers were selected.

CONCLUSIONS

The search strategy for determining candidate best papers for an IMIA Yearbook's section is now explicitly specified and allows for reproducibility. However, some aspects of the whole process remain reviewer-dependent, mostly because there is no characterization of a "best paper".

An overview of medical informatics education in China

OBJECTIVE

To outline the history of medical informatics education in the People's Republic of China, systematically analyze the current status of medical informatics education at different academic levels (bachelor's, master's, and doctoral), and suggest reasonable strategies for the further development of the field in China.

METHOD

The development of medical informatics education was divided into three stages, defined by changes in the specialty's name. Systematic searches of websites for material related to the specialty of medical informatics were then conducted. For undergraduate education, the websites surveyed included the website of the Ministry of Education of the People's Republic of China (MOE) and those of universities or colleges identified using the baidu.com search engine. For postgraduate education, the websites included China's Graduate Admissions Information Network (CGAIN) and the websites of the universities or their schools or faculties. Specialties were selected on the basis of three criteria: (1) for undergraduate education, the name of specialty or program was medical informatics or medical information or information management and information system; for postgraduate education, medical informatics or medical information; (2) the specialty was approved and listed by the MOE; (3) the specialty was set up by a medical college or medical university, or a school of medicine of a comprehensive university. The information abstracted from the websites included the year of program approval and listing, the university/college, discipline catalog, discipline, specialty, specialty code, objectives, and main courses.

RESULTS AND CONCLUSIONS

A total of 55 program offerings for undergraduate education, 27 for master's-level education, and 5 for PhD-level education in medical informatics were identified and assessed in China. The results indicate that medical informatics education, a specialty rooted in medical library and information science education in China, has grown significantly in that country over the past 10 years. Frequent changes in the specialty's name and an unclear identity have hampered the visibility of this educational specialty and impeded its development. There is a noticeable imbalance in the distribution of degree programs in medical informatics in different disciplines, with the majority falling under information management. There is also an uneven distribution of the specialty settings of medical informatics at the various academic levels (bachelor's, master's, and doctoral). In addition, the objectives and curriculum design of medical informatics education differ from one university to another and also from those of foreign universities or colleges. It is recommended that China (1) treat medical informatics as a priority "must-have" discipline to build in China, (2) establish its own independent, balanced degree programs, (3) set up a specialty of "medical informatics" under the "medicine" category, (4) explore curriculum integration with international medical informatics education, and (5) establish and improve medical informatics education system.

MIARS: a medical image retrieval system

The next generation of medical information system will integrate multimedia data to assist physicians in clinical decision-making, diagnoses, teaching, and research. This paper describes MIARS (Medical Image Annotation and Retrieval System). MIARS not only provides automatic annotation, but also supports text based as well as image based retrieval strategies, which play important roles in medical training, research, and diagnostics. The system utilizes three trained classifiers, which are trained using training images. The goal of these classifiers is to provide multi-level automatic annotation. Another main purpose of the MIARS system is to study image semantic retrieval strategy by which images can be retrieved according to different levels of annotation.

Integrating imaging informatics into the radiology residency curriculum: rationale and example curriculum

Imaging informatics, as part of the wider emerging discipline of medical informatics, remains poorly defined. However, many educators agree that formalized and flexible training in the collection, display, manipulation, storage, retrieval, and communication of imaging data, as well as the integration of these data into larger databases, should be introduced into the period of radiology residency training. The authors review the importance of such training to those individuals now preparing for clinical practice and research. They describe a sample imaging informatics curriculum that can be incorporated into a 4-year radiology residency program and the significance of such training in establishing a new subdiscipline focusing on imaging information technologies.

Biomedical Imaging Research Opportunities Workshop III: A White Paper

The third Biomedical Imaging Research Opportunities Workshop (BIROW III) was held on March 11-12, 2005, in Bethesda, MD. The workshop addressed four areas of imaging that present opportunities for research and development: Multimodality Image-Guided Therapy, Imaging Informatics, Imaging Cell Trafficking, and Technology Improvement and Commercialization. The first three areas were individually addressed in their own plenary sessions, followed by audience discussions that explored research opportunities and challenges. This paper synthesizes these discussions into a strategy for future research directions in biomedical imaging.

A review of content-based image retrieval systems in medical applications-clinical benefits and future directions

Content-based visual information retrieval (CBVIR) or content-based image retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. The availability of large and steadily growing amounts of visual and multimedia data, and the development of the Internet underline the need to create thematic access methods that offer more than simple text-based queries or requests based on matching exact database fields. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of differing sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever-increasing quantities and used for diagnostics and therapy. The Radiology Department of the University Hospital of Geneva alone produced more than 12,000 images a day in 2002. The cardiology is currently the second largest producer of digital images, especially with videos of cardiac catheterization ( approximately 1800 exams per year containing almost 2000 images each). The total amount of cardiologic image data produced in the Geneva University Hospital was around 1 TB in 2002. Endoscopic videos can equally produce enormous amounts of data. With digital imaging and communications in medicine (DICOM), a standard for image communication has been set and patient information can be stored with the actual image(s), although still a few problems prevail with respect to the standardization. In several articles, content-based access to medical images for supporting clinical decision-making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into picture archiving and communication systems (PACS) have been created. This article gives an overview of available literature in the field of content-based access to medical image data and on the technologies used in the field. Section 1 gives an introduction into generic content-based image retrieval and the technologies used. Section 2 explains the propositions for the use of image retrieval in medical practice and the various approaches. Example systems and application areas are described. Section 3 describes the techniques used in the implemented systems, their datasets and evaluations. Section 4 identifies possible clinical benefits of image retrieval systems in clinical practice as well as in research and education. New research directions are being defined that can prove to be useful. This article also identifies explanations to some of the outlined problems in the field as it looks like many propositions for systems are made from the medical domain and research prototypes are developed in computer science departments using medical datasets. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text-based retrieval methods as they exist at the moment but to complement them with visual search tools.

Developing and evaluating criteria to help reviewers of biomedical informatics manuscripts

Peer-reviewed publication of scientific research results represents the most important means of their communication. The authors have annually reviewed a large heterogeneous set of papers to produce the International Medical Informatics Association (IMIA) Yearbook of Medical Informatics. To support an objective and high-quality review process, the authors attempted to provide reviewers with a set of refined quality criteria, comprised of 80 general criteria and an additional 60 criteria for specific types of manuscripts. Authors conducted a randomized controlled trial, with 18 reviewers, to evaluate application of the refined criteria on review outcomes. Whereas the trial found that reviewers applying the criteria graded papers more strictly (lower overall scores), and that junior reviewers appreciated the availability of the criteria, there was no overall change in the interrater variability in reviewing the manuscripts. The authors describe their experience as a "case report" and provide a reference to the refined quality review criteria without claiming that the criteria represent a validated instrument for quantitative quality measurement.