Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery-Reference-Cited by-同舟云学术

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery

Published:2019-11-29 Issue:1 Volume:61 Page:39-48
ISSN:0013-9580
Container-title:Epilepsia
language:en
Short-container-title:Epilepsia

Author:

Wissel Benjamin D.¹^ORCID,Greiner Hansel M.²³,Glauser Tracy A.²³,Holland‐Bouley Katherine D.²³,Mangano Francesco T.²⁴,Santel Daniel¹,Faist Robert¹,Zhang Nanhua²⁵,Pestian John P.¹²,Szczesniak Rhonda D.²⁵,Dexheimer Judith W.¹²⁶

Affiliation:

1. Department of Biomedical Informatics Cincinnati Children’s Hospital Medical Center Cincinnati Ohio

2. Department of Pediatrics University of Cincinnati College of Medicine Cincinnati Ohio

3. Division of Neurology Cincinnati Children’s Hospital Medical Center Cincinnati Ohio

4. Division of Neurosurgery Cincinnati Children’s Hospital Medical Center Cincinnati Ohio

5. Division of Biostatistics & Epidemiology Cincinnati Children’s Hospital Medical Center Cincinnati Ohio

6. Division of Emergency Medicine Cincinnati Children’s Hospital Medical Center Cincinnati Ohio

Funder

National Heart, Lung, and Blood Institute

Agency for Healthcare Research and Quality

Publisher

Wiley

Subject

Neurology (clinical),Neurology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/epi.16398

Reference47 articles.

1. Early Identification of Refractory Epilepsy

2. The Cost of Epilepsy in the United States: An Estimate from Population-Based Clinical and Survey Data

3. Epilepsy surgery: eligibility criteria and presurgical evaluation;Ryvlin P;Dialogues Clin Neurosci,2008

4. A Randomized, Controlled Trial of Surgery for Temporal-Lobe Epilepsy

5. Seizure outcome after epilepsy surgery in children and adolescents

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