{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T06:49:41Z","timestamp":1787726981694,"version":"build-2784847793"},"reference-count":21,"publisher":"Scientific Scholar","content-domain":{"domain":["surgicalneurologyint.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"\n Background:<\/jats:title>\n Primary headaches are widespread and costly public health problems. However, there are insufficient medical resources for their treatment in Japan due to two reasons. First, the numbers of headache specialists and clinics remain insufficient. Second, neurologists and neurosurgeons mainly treat headaches in Japan. However, they mainly work as general stroke neurologists, so they cannot focus on primary headache treatment. To solve these problems, we preliminarily developed a deep learning (DL)-based automated diagnosis model from patients\u2019 Japanese unstructured sentences in the medical questionnaire using a DL framework. We hypothesized that the model would reduce the time and burden on both doctors and patients and improve their quality of life.<\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n We retrospectively investigated our primary headache database and developed a diagnosis model using the DL framework (Prediction One, Sony Network Communications Inc., Japan). We used age, sex, date, and embedding layer made by the medical questionnaire\u2019s natural language processing (NLP).<\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n Eight hundred and forty-eight primary headache patients (495 women and 353 men) are included. The median (interquartile range) age was 59 (40\u201374). Migraine accounted for 46%, tension-type headache for 47%, trigeminal autonomic cephalalgias for 5%, and other primary headache disorders for 2%. The accuracy, mean precision, mean recall, and mean F value of the developed diagnosis model were 0.7759, 0.8537, 0.6086, and 0.6353, which were satisfactory.<\/jats:p>\n <\/jats:sec>\n \n Conclusion:<\/jats:title>\n The DL-based diagnosis model for primary headaches using the raw medical questionnaire\u2019s Japanese NLP would be useful in performing efficient medical practice after ruling out the secondary headaches.<\/jats:p>\n <\/jats:sec>","DOI":"10.25259\/sni_827_2020","type":"journal-article","created":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T03:24:45Z","timestamp":1609212285000},"page":"475","update-policy":"https:\/\/doi.org\/10.25259\/crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Preliminary development of a deep learning-based automated primary headache diagnosis model using Japanese natural language processing of medical questionnaire"],"prefix":"10.25259","volume":"11","author":[{"given":"Masahito","family":"Katsuki","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norio","family":"Narita","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasuhiko","family":"Matsumori","sequence":"additional","affiliation":[{"name":"Sendai Headache and Neurology Clinic, Sendai, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naoya","family":"Ishida","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ohmi","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siqi","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Teiji","family":"Tominaga","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Tohoku University Graduate School of Medicine, Aobaku, Sendai, Miyagi, Japan."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10894","published-online":{"date-parts":[[2020,12,29]]},"reference":[{"key":"10.25259\/SNI_827_2020\/ref-1","first-page":"126","article-title":"Identifying peripheral arterial disease cases using natural language processing of clinical 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