{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T05:03:43Z","timestamp":1751691823053,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>Electronic Health Records (EHRs) conceal a hidden knowledge that could be mined with data science tools. This is relevant for N.N. Burdenko Neurosurgery Center taking the advantage of a large EHRs archive collected for a period between 2000 and 2017. This study was aimed at testing the informativeness of neurosurgical operative reports for predicting the duration of postoperative stay in a hospital using deep learning techniques. The recurrent neuronal networks (GRU) were applied to the word-embedded texts in our experiments. The mean absolute error of prediction in 90% of cases was 2.8 days. These results demonstrate the potential utility of narrative medical texts as a substrate for decision support technologies in neurosurgery.<\/jats:p>","DOI":"10.3233\/978-1-61499-959-1-125","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T08:47:32Z","timestamp":1740127652000},"source":"Crossref","is-referenced-by-count":1,"title":["Prediction of Postoperative Hospital Stay with Deep Learning Based on 101 654 Operative Reports in Neurosurgery"],"prefix":"10.3233","author":[{"family":"Danilov Gleb","sequence":"additional","affiliation":[]},{"family":"Kotik Konstantin","sequence":"additional","affiliation":[]},{"family":"Shifrin Michael","sequence":"additional","affiliation":[]},{"family":"Strunina Uliya","sequence":"additional","affiliation":[]},{"family":"Pronkina Tatyana","sequence":"additional","affiliation":[]},{"family":"Potapov Alexander","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","ICT for Health Science Research"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T09:03:02Z","timestamp":1740128582000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-958-4&spage=125&doi=10.3233\/978-1-61499-959-1-125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-959-1-125","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2019]]}}}