Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL.

BACKGROUND: For standardization of terms in the reports of medical device adverse events, 89 Japanese medical device adverse event terminologies were published in March 2015. The 89 terminologies were developed independently by 13 industry associations, suggesting that there may be inconsistencies among the terms proposed. The purpose of this study was to integrate the 89 sets of terminologies and evaluate inconsistencies among them using SPARQL. METHODS: In order to evaluate the inconsistencies among the integrated terminology, the following six items were evaluated: (1) whether the two-layer structure between category term and preferred term is consistent, (2) whether synonyms of a preferred term are involved. Reversing the layer-category order of matching was also performed, (3) whether each preferred term is subordinate to only one category term, (4) whether the definitions of terms are uniquely determined, (5) whether CDRH-NCIt terms corresponding to preferred terms are uniquely determined, (6) whether a term in a medical device problem is used for patient problems. RESULTS: About 60% of the total number of duplicated terms were found. This is because industry associations that created multiple terminologies adopted the same terms in terminologies of similar medical device groups. In the case that all terms with the same spelling have the same concept, efficient integration can be achieved automatically using RDF. Furthermore, we evaluated six matters of inconsistency in this study, terms that need to be reviewed accounted for about 10% or less than 10% in each item. CONCLUSIONS: The RDF and SPARQL were useful tools to explore inconsistencies of hierarchies, definition statements, and synonyms when integrating terminolgy by term notation, and these had the advantage of reducing the physical and time burden.

Changing Emotions About Fukushima Related to the Fukushima Nuclear Power Station Accident-How Rumors Determined People's Attitudes: Social Media Sentiment Analysis.

BACKGROUND: Public interest in radiation rose after the Tokyo Electric Power Company (TEPCO) Fukushima Daiichi Nuclear Power Station accident was caused by an earthquake off the Pacific coast of Tohoku on March 11, 2011. Various reports on the accident and radiation were spread by the mass media, and people displayed their emotional reactions, which were thought to be related to information about the Fukushima accident, on Twitter, Facebook, and other social networking sites. Fears about radiation were spread as well, leading to harmful rumors about Fukushima and the refusal to test children for radiation. It is believed that identifying the process by which people emotionally responded to this information, and hence became gripped by an increased aversion to Fukushima, might be useful in risk communication when similar disasters and accidents occur in the future. There are few studies surveying how people feel about radiation in Fukushima and other regions in an unbiased form. OBJECTIVE: The purpose of this study is to identify how the feelings of local residents toward radiation changed according to Twitter. METHODS: We used approximately 19 million tweets in Japanese containing the words "radiation" (), "radioactivity" (), and "radioactive substances" () that were posted to Twitter over a 1-year period following the Fukushima nuclear accident. We used regional identifiers contained in tweets (ie, nouns, proper nouns, place names, postal codes, and telephone numbers) to categorize them according to their prefecture, and then analyzed the feelings toward those prefectures from the semantic orientation of the words contained in individual tweets (ie, positive impressions or negative impressions). RESULTS: Tweets about radiation increased soon after the earthquake and then decreased, and feelings about radiation trended positively. We determined that, on average, tweets associating Fukushima Prefecture with radiation show more positive feelings than those about other prefectures, but have trended negatively over time. We also found that as other tweets have trended positively, only bots and retweets about Fukushima Prefecture have trended negatively. CONCLUSIONS: The number of tweets about radiation has decreased overall, and feelings about radiation have trended positively. However, the fact that tweets about Fukushima Prefecture trended negatively, despite decreasing in percentage, suggests that negative feelings toward Fukushima Prefecture have become more extreme. We found that while the bots and retweets that were not about Fukushima Prefecture gradually trended toward positive feelings, the bots and retweets about Fukushima Prefecture trended toward negative feelings.

[Investigation of Research Trends in Radiological Technology Using Text Mining].

The purpose of this study was to investigate the trends of researches regarding radiological technology. We collected research papers published from 2007 to 2017 from Japanese Society of Radiological Technology (JSRT). After preprocessing, we performed morphological analysis using terminology from Japan Radiological Society, Japan Society of Medical Physics, and JSRT to extract technical terms. Furthermore, we calculated the Jaccard similarity coefficient to represent the similarity between two terms. This value ranged from 0 to 1, where 0 implied that the terms were completely dissimilar. Finally, in order to detect terms that characteristically appear in each year, we visualized co-occurring terms by using network diagrams. From the morphological analysis, 5471 technical terms were extracted. The most frequency term was "image" from 2007 to 2017. "Phantom" and "CT" were frequent terms after "image." In addition, the number of research papers including "image," "phantom," and "CT" were increasing. For network analysis, the characteristic terms in 2007 were "filter" and "HU"; those in 2012 were "dimension," "standard deviation,"and "artifact"; and those in 2017 were "PET," "scattered ray," and "collimator." In conclusion, the highest interest research topic in radiological technology was "image," and recently, there has been a tendency to be interested in topics related to nuclear medicine.

[Evaluation of the Automatic Full Form Retrieval Method from Abbreviation Using Word2vec for Terminology Expansion].

PURPOSES: The purposes of this study were to automatically extract full forms from abbreviations by using Word2vec for terminology expansion and determine the optimal parameters that ensure the highest accuracy. METHODS: Approximately 300000 English abstracts on "image diagnosis" were collected using PubMed from January 1994 to December 2018. As preprocessing, all uppercase letters in the collected data were converted to lowercase letters, and symbols were deleted. In addition, compound word recognition was performed using RadLex published by the Radiological Society of North America and the abbreviation collection published by the Japanese Society  of  Radiological  Technology.  Next,  distributed  representations  were  generated  by  two  algorithms, continuous bag-of-words (CBOW) and Skip-gram, by using the following parameters: iteration numbers (3-85) and dimensions of word vectors (50-1000). Abbreviations were input to the generated distributed representations, and full forms with the highest cosine similarities with the abbreviations were identified. Then, the rates of the correct answers were calculated by comparing the predicted full forms to 214 gold standards extracted from the abbreviation collection. RESULTS: The highest correct answer rate was 74.3% by Skip-gram, 200 dimensions and 10 iterations. This rate was higher in Skip-gram than in CBOW for all the tested conditions. CONCLUSION: The accuracy of extracting the full forms by Word2vec is 74.3%, and this result contributes to the consistency of a terminology and the efficiency of terminology expansion.

[Assessing Visual Attention of Mammography Positioning Using Eye Tracking System: A Comparison between Experts and Novices].

A common cause for image retakes in mammography is lack of proper positioning. Image retake is a potential hazard of increased radiation exposure to patient, patient discomfort and pain. Therefore, a mammographer has to provide fast exams with fewer retakes. Although evaluation of how a mammographer is effectively positioning has been studied in many ways, little research has been conducted to analyze visual attention. In this study, eye tracking system was adopted to detect eye movements and locations within a participants' visual fields during positioning. Eye tracking system has been widely used for assessing technical skills and risk awareness, and for comparing the skills between experts and novices. Two skilled mammographers and two novices were recruited. Positioning related activities were divided into two phases: patient's observation and breast positioning. Breast positioning was sub-divided into three stages to compare visual attention between experts and novices using heatmap and gaze plot. Although the expert tended to check each point, the novices tended to have a relatively short gaze of the outer breast region was observed. In the future, a comparative evaluation using clinical images is necessary; however, the eye tracking system to visualize attention contributes to medical safety during positioning.

[Appling Text-mining to Extracting Technical Terms from Textbooks-Toward Updating the Terminology in the Field of Radiology Technology].

Although terminology requires continuous consideration of recorded technical terms, extracting these terms manually is difficult, because the number of recorded terms is constantly increasing. Text-mining acquires information from numerous documents, and is capable of extracting technical terms. The purpose of this study is to extract candidate terms using text-mining toward updating the terminology of Japanese society of radiological technology (JSRT). First, the subjects for this study were textbooks published by the JSRT, and morphological analysis was conducted, which is an analysis to break the books up into meaningful words. Additionally, index terms of textbooks were extracted. Second, we observed overlaps between the JSRT technical terms and the terms obtained from the morphological analysis and the indexes of textbooks and the extracted terms were absent in the JSRT terminology. The overlap was 53.6% (3090/5770 terms). The terms, "imaging technology for magnetic resonance" and "information and system in radiological technology" were missing from the JSRT terminology. From these results, it was estimated that half number of the JSRT technical terms were changing with time. This study demonstrated that text mining showed the differences between old and new technical terms.

Investigation of Preferences in Working Environment of Radiological Technologists Using Conjoint Analysis.

The purpose of this study is to assess working environment preferences of radiological technologists using conjoint analysis. We carried a questionnaire survey on working environment preferences for 200 radiological technologists working in medical facilities in Japan. We defined eight characteristics for virtual medical facilities as follows: presence of colleagues who can be consulted, employment status, number of overtime work per month, academic meeting participation, number of hospital beds, presence of nuclear medicine imaging systems and radiation therapy systems, location of medical facilities, and change rate in annual income. A total of 18 virtual medical facilities were selected by an orthogonal array table using above-mentioned characteristics. The acquired data by the pairwise comparison method were analyzed by conjoint analysis. Marginal rates of substitution between income and non-pecuniary characteristics, which represent radiological technologists' preferences, were also calculated. The factors influenced on their preferences were the following: employment status is not part-time, medical facility is smaller in scale, nuclear medicine imaging systems and radiation therapy systems are set up, and the number of overtime work is less. It was suggested that radiological technologists have a tendency to avoid increase of workloads and select his/her working place with emphasis on own experiences.

[Comparison of Japanese Notation and Meanings among Three Terminologies in Radiological Technology Domain].

PURPOSE: The purpose of this study is to investigate the differences in the notation of technical terms and their meanings among three terminologies in Japanese radiology-related societies. MATERIALS AND METHODS: The three terminologies compared in this study were "radiological technology terminology" and its supplement published by the Japan Society of Radiological Technology, "medical physics terminology" published by the Japan Society of Medical Physics, and "electric radiation terminology" published by the Japan Radiological Society. Terms were entered into spreadsheets and classified into the following three categories: Japanese notation, English notation, and meanings. In the English notation, terms were matched to character strings in the three terminologies and were extracted and compared. The Japanese notations were compared among three terminologies, and the difference between the meanings of the two terminologies radiological technology terminology and electric radiation terminology were compared. RESULTS AND DISCUSSION: There were a total of 14,982 terms in the three terminologies. In English character strings, 2,735 terms were matched to more than two terminologies, with 801 of these terms matched to all the three terminologies. Of those terms in English character strings matched to three terminologies, 752 matched to Japanese character strings. Of the terms in English character strings matched to two terminologies, 1,240 matched to Japanese character strings. With regard to the meanings category, eight terms had mismatched meanings between the two terminologies. For these terms, there were common concepts between two different meaning terms, and it was considered that the derived concepts were described based on domain.

Trends for the Geographic Distribution of Radiological Resources in Hokkaido, Japan: Data Analysis Using Gini Coefficient and Herfindahl-Hirschman Index.

The aim of this study is to analyze the maldistribution and the trends in the geographic distribution of radiological resources in secondary medical areas of Hokkaido. The distribution was measured by combining the Gini coefficient (GC), which is an indicator of inequality of distribution, and the Herfindahl-Hirschman index (HHI), which is mainly used to assess market concentration. Data concerning the distribution of radiological resources, such as CT, MRI, radiotherapy facilities (RTF), radiological technologists (RT), and medical doctors were obtained from official publications. CT was more equally distributed, and RTF was more inequality than other radiological resources in 2014. Radiological resources excluded CT were higher degree of concentration than population distribution, and it showed that they were located relatively more intensively in urban areas than in rural areas. During the period 1999-2014, the GC for CT, MRI, RTF, and RT decreased, while the HHI increased. These trends indicated increased equality of distribution of CT, MRI, RTF, and RT and the concentration in urban areas. This study suggested that GC and HHI could be powerful indicators for allocation planning of medical resources with further analysis of the maldistribution of medical resources.

Development of a Knowledge-based Application Utilizing Ontologies for the Continuing Site-specific JJ1017 Master Maintenance.

The purpose of this study was to develop the JJ1017 Knowledge-based Application (JKA) to support the continuing maintenance of a site-specific JJ1017 master defined by the JJ1017 guideline as a standard radiologic procedure master for medical information systems that are being adopted by some medical facilities in Japan. The method consisted of the following three steps: (1) construction of the JJ1017 Ontology (JJOnt) as a knowledge base using the Hozo (an environment for building/using ontologies); (2) development of modules (operation, I/O, graph modules) that are required to continue the maintenance of a site-specific JJ1017 master; and (3) unit testing of the JKA that consists of the JJOnt and the modules. As a result, the number of classes included in the JJOnt was 21,697. Within the radiologic procedure classes included in the above, the ratio of a JJ1017 master code for an external beam radiotherapy was the highest (51%). In unit testing of the JKA, we checked the main operations (e.g., keyword search of a JJ1017 master code/code meaning, editing the description of classes, etc.). The JJOnt is a knowledge base for implementing features that medical technologists find necessary in medical information systems. To enable medical technologists to exchange/retrieve semantically accurate information while using medical information systems in the future, we expect the JKA to support the maintenance and improvement of the site-specific JJ1017 master.

[Classifying Ontology towards an Application for Radiological Technology].

This study aims to grasp the target area of the literature on ontology and to apply it in radiological technology. We used Google scholar to search the literature containing the keyword "ontology". Our search identified and extracted 162,381 words from 29 manuscripts and used the 8,706 nouns excluding duplicates as individual variable. Using a cluster analysis, we categorized the documents to one of the following five classifications: (1) "Systematization of vocabulary by text mining", (2) "Hierarchy of language information", (3) "Conceptualization of situation", (4) "Standardization of lexical information", and (5) "Visualization of the concepts related to the problem". We propose that the terminologies in (2), (4), and (5) cluster can be used in radiological technology field.

[An analysis of existing terminology towards constructing ontology in the field of the radiological technology].

PURPOSE: In 1994, Japanese Society of Radiological Technology (JSRT) constructed the lexicon in the field of radiologic technology. However, recently, latest lexicon is not updated yet. The purpose of this article is to compare the terminologies in clinical medicine with the others and to consider reconstructing the lexicon in the radiological technology. MATERIALS AND METHODS: Our study selected three categories from the database of the academic society. These three groups were Clinical medicine (hereafter CM, 167 societies, includes JSRT), Psychology / Education (hereafter P/E, 104 societies), and Comprehensive synthetic engineering (hereafter CSE, 40 societies). First, all societies were surveyed to know whether there were any lexicon in their official website. Second, these terminologies were surveyed on the following criteria: (a) Media of lexicon, (b) Number of terms, (c) File type of lexicon, (d) Terms translated into English, (e) Way of searching terms, and (f) Number of committees of the terminology. RESULTS: Lexicon in CM, P/E, and CSE had 20, 4, and 7. Compared with P/E and CSE, CM showed the following trends: (a) used electronic media frequently, (b) stored large number of terms (about 5,000 to 11,000), (c) enabled to download frequently, and (d) used the alphabet and Japanese syllabary order frequently. CONCLUSIONS: Compared with the lexicon of P/E and CSE, terminology in CM tended to adopt the electronic media of lexicon and to have large number of terms. Additionally, many lexicons were expressed in English terms along with Japanese terms. Following massive lexicon of SNOMED-CT and RadLex, it is necessary to consider applying the web-based term searching and an ontological technique to the lexicon of radiological technology.

Answering Japanese Fill-in-the-Blank Questions in the Radiological Technology Field Using BERT.

The purpose of this study was to evaluate the accuracy of Japanese fill-in-the-blank questions in the radiological technology field using six BERT models. Our original model, created using 330,000 abstracts related to radiological technology, was as accurate as other models created by Wikipedia when vocabulary size was the same. Further improvements in accuracy can be expected if we can increase the vocabulary size and add Japanese Wikipedia data in training.

Demonstration of Japanese radiographic examination codes in establishing typical values for a wide variety of general radiography examinations.

The purpose of this study was to demonstrate Japanese radiographic examination codes JJ1017 in establishing typical values for a wide variety of general radiography. About 200,000 sets of examination data were collected, including exposure conditions, JJ1017 code applied, examination room numbers and patient information. Typical values for adults, children, and infants were calculated from the collected data, and the following items were examined: comparing typical values of general radiography in Japan DRLs 2015 and typical values in a facility; comparison of typical values between X-ray equipment for examinations of DRLs 2015; comparison of typical values for different procedures at the same anatomical site; identification of examination items associated with high radiation doses. The total numbers of JJ1017 codes applicable to the examinations were 45,372 for adults, 542 for children, and 2339 for infants. To calculate the typical values and compare these with the DRLs, we used a combination of JJ1017 anatomical codes, posture codes, and direction of radiation codes. The combination of these codes allowed the calculation of a typical value and comparison with DRLs 2015. Comparison between devices reveals differences in radiation doses and provides an opportunity to review the characteristics of the devices and their operation to suggest dose reductions. By calculating typical values for examination items for which the DRLs were not available, we were able to identify examination items with high doses in a facility and suggest items that should be audited in the facility.

Evaluation of Machine Translation Accuracy Focused on the Adverse Event Terminology for Medical Devices.

The purpose of this study was to evaluate the accuracy of deep neural machine translation focused on medical device adverse event terminology. 10 models were obtained, and their English-to-Japanese translation accuracy was evaluated using quantitative and qualitative measures. No significant difference was found in the quantitative index except for a few pairs. In the qualitative evaluation, there was a significant difference and googletrans and GPT-3 were regarded as useful models.

Comparison of the accuracy of Japanese synonym identifications using word embeddings in the radiological technology field.

The terminology in radiological technology is crucial, encompassing a broad range of principles from radiation to medical imaging, and involving various specialists. This study aimed to evaluate the accuracy of automatic synonym detection considering the characteristics of the Japanese language by Word2vec and fastText in the radiological technology field for the terminology elaboration. We collected around 340 thousand abstracts in Japanese. First, preprocessing of the abstract data was performed. Then, training models were created with Word2vec and fastText with different architectures: continuous bag-of-words (CBOW) and skip-gram, and vector sizes. Baseline synonym sets were curated by two experts, utilizing terminology resources specific to radiological technology. A term in the dataset input into the generated models, and the top-10 synonym candidates which had high cosine similarities were obtained. Subsequently, precision, recall, F1-score, and accuracy for each model were calculated. The fastText model with CBOW at 300 dimensions was most precise in synonym detection, excelling in cases with shared n-grams. Conversely, fastText with skip-gram and Word2vec were favored for synonyms without common n-grams. In radiological technology, where n-grams are prevalent, fastText with CBOW proved advantageous, while in informatics, characterized by abbreviations and transliterations, Word2vec with CBOW was more effective.

[Inter-rater Reliability and Cost in Pricing for Creating Dataset Focused on Mediolateral Oblique View in Mammography].

PURPOSE: The purpose of this study was to assess inter-rater reliability and workload for creating accurate training data in the clinical evaluation of mammographic positioning for deep learning. METHODS: A total of 107 mammographic images without lesions were labeled by two certified radiologic technologists in seven items: six clinical image evaluation criteria in positioning and breast tissue density. The kappa coefficient was calculated as an indicator of interrater reliability. Furthermore, the labeling cost per image was calculated based on labeling time and salary for the technologists. RESULTS: The kappa coefficients were 0.71 for inframammary fold, 0.43 for nipple in profile, 0.45 for great pectoral muscle, 0.10 for symmetrical images, and 0.61 for retromammary fat. No significant difference was found in the coefficients of spread of breast tissue. The cost per image was calculated at 11.0 yen. CONCLUSION: The inter-rater reliability for the inframammary fold, nipple in profile, great pectoral muscle, and retromammary fat ranged from "moderate" to "substantial." The reliability for symmetrical images was "slight," indicating the need for a consensus among evaluators during labeling. The labeling cost was equivalent to or higher than that of existing services.

t-SNE Visualization of Vector Pairs of Similar and Dissimilar Definition Sentences Created by Word2vec and Doc2vec in Japanese Medical Device Adverse Event Terminology.

The purpose of our study is to identify the patterns of vectors in similar/dissimilar pairs of definition sentence created by Word2vec and doec2vec for elaboration of the terminology for Japanese Medical Device Adverse Events. 2-dimension vector space created by t-SNE showed that the pair with true positive located closer in a vector space, especially Doc2vec had a strong tendency. Comparing with Word2vec, Similar vectors in Doc2vec were close and tended to form clusters.