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Dexheimer, Judith W.

Early identification of epilepsy surgery candidates: A multicenter, machine learning study.

Citation
Wissel BD, Greiner HM, Glauser TA, Pestian JP, Kemme AJ, Santel D, Ficker DM, Mangano FT, Szczesniak RD, Dexheimer JW. Early identification of epilepsy surgery candidates: A multicenter, machine learning study. Acta Neurol Scand. 2021 Jul;144(1):41-50. doi: 10.1111/ane.13418. Epub 2021 Mar 26. PMID: 33769560; PMCID: PMC8178229.
Principal Investigator
Dexheimer, Judith W.
Project Name
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

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

Citation
Wissel BD, Greiner HM, Glauser TA, Holland-Bouley KD, Mangano FT, Santel D, Faist R, Zhang N, Pestian JP, Szczesniak RD, Dexheimer JW. Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Epilepsia. 2019 Nov 29. doi: 10.1111/epi.16398. [Epub ahead of print]. PMID: 31784992.
Principal Investigator
Dexheimer, Judith W.
Project Name
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.

Citation
Wissel BD, Greiner HM, Glauser TA, Mangano FT, Santel D, Pestian JP, Szczesniak RD, Dexheimer JW. Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Epilepsia. 2019 Sep;60(9):e93-e98. doi: 10.1111/epi.16320. Epub 2019 Aug 23. PMID: 31441044.
Principal Investigator
Dexheimer, Judith W.
Project Name
Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients