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National survey of international electives for global health in undergraduate medical education in Japan, 2011-2014.
Authors: Suzuki T, Nishigori H Abstract Interest in global health in medical education is increasing in Western countries, whereas data from non-Western countries is scarce. Here, we conducted a nationwide study of international clinical electives at Japanese medical schools from 2011 to 2013. We constructed a 28-item cross-sectional survey in Japanese to investigate the rate and characteristics of both Japanese students going abroad and international students coming on exchange to Japan. The surveys were sent to the administrative offices of all 80 Japanese medical schools in each of the three years, through the J...
Source: Nagoya Journal of Medical Science - March 29, 2018 Category: International Medicine & Public Health Tags: Nagoya J Med Sci Source Type: research

A Scottish and Japanese experience of patient-centred diabetic care: descriptive study of interprofessional education on live webinar.
In conclusion, all participants learned that interprofessional collaboration was clearly required for diabetes management focused on patient-centred care. All participants appreciated the differences in the approach of the two countries involved because of the cultural- and health related differences. This programme was significant in raising awareness regarding the need for international interprofessional intervention on diabetes towards developing a model for live webinar IIPE. PMID: 30587861 [PubMed - in process]
Source: Nagoya Journal of Medical Science - December 29, 2018 Category: International Medicine & Public Health Tags: Nagoya J Med Sci Source Type: research

Usefulness of web search queries for early detection of diseases in infants
This study evaluates the usefulness of web searches in predicting diseases in order to encourage guardians to consult a doctor promptly if their children are ill. We collected six months of search queries from Yahoo! JAPAN Search between October 2016 and March 2017. Using a machine learning model, we investigated the accuracy of the search query's ability to predict the diagnosis of biliary atresia and hypertrophic pyloric stenosis. Both diseases were modeled with an accuracy of approximately 80%, and symptoms related to the disease were significant features in the model. These findings suggest the possibility of detecting...
Source: Nagoya Journal of Medical Science - March 17, 2021 Category: International Medicine & Public Health Authors: Shuji Yamaguchi Akinari Hinoki Kota Tsubouchi Hizuru Amano Akira Tajima Hiroo Uchida Source Type: research

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