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Developing Predictive Models to Anticipate Shunt Complications in 33,248 Pediatric Patients with Shunted Hydrocephalus Utilizing Machine Learning.

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Title: Developing Predictive Models to Anticipate Shunt Complications in 33,248 Pediatric Patients with Shunted Hydrocephalus Utilizing Machine Learning.
Authors: Shahrestani, Shane1,2 (AUTHOR), Shlobin, Nathan3 (AUTHOR), Gendreau, Julian L.4 (AUTHOR), Brown, Nolan J5 (AUTHOR), Himstead, Alexander6 (AUTHOR), Patel, Neal A7 (AUTHOR), Pierzchajlo, Noah8 (AUTHOR), Chakravarti, Sachiv9 (AUTHOR), Lee, Darrin Jason1 (AUTHOR), Chiarelli, Peter A.1 (AUTHOR), Bullis, Carli L.1 (AUTHOR), Chu, Jason1 (AUTHOR)
Source: Pediatric Neurosurgery. 2023, Vol. 58 Issue 4, p206-214. 9p.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22Pediatric+Neurosurgery%22">Pediatric Neurosurgery</searchLink>. 2023, Vol. 58 Issue 4, p206-214. 9p.
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              Text: 2023
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