Assessing the reliability of zygomatic bone landmarks as guides to reach the inferior orbital fissure in orbitozygomatic osteotomy: anatomical study of 83 human skulls.

To perform an adequate orbitozygomatic craniotomy, it is very important that the bone cut which passes through the body of the zygoma reaches the inferior orbital fissure (IOF). To reach the IOF, two surface landmarks on the body of the zygoma are described: a point located directly superior to the malar eminence and the zygomaticofacial foramen. The article explores the reliability of these landmarks and three other alternative points to reach the IOF.

Predicting Postoperative Hospital Stay in Neurosurgery with Recurrent Neural Networks Based on Operative Reports.

This study aimed to predict the duration of the postoperative in-hospital period in neurosurgery based on unstructured operative reports, natural language processing, and deep learning. The recurrent neuronal network (RNN-GRU) was tuned on the word-embedded reports of primary surgical cases retrieved for the period between 2000 and 2017. A new test dataset obtained for the primary operations performed in 2018-2019 was used to evaluate model performance.

An Information Extraction Algorithm for Detecting Adverse Events in Neurosurgery Using Documents Written in a Natural Rich-in-Morphology Language.

Rich-in-morphology language, such as Russian, present a challenge for extraction of professional medical information. In this paper, we report on our solution to identify adverse events (complications) in neurosurgery based on natural language processing and professional medical judgment. The algorithm we proposed is easily implemented and feasible in a broad spectrum of clinical studies.

Prediction of Postoperative Hospital Stay with Deep Learning Based on 101 654 Operative Reports in Neurosurgery.

Electronic Health Records (EHRs) conceal a hidden knowledge that could be mined with data science tools. This is relevant for N.N.