Daniel Goldenholz

Physician Scientist / Assistant Professor

Beth Israel Deaconess Medical Center

United States

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About

Daniel Goldenholz is a Physician Scientist and Assistant Professor at Beth Israel Deaconess Medical Center in the United States. His research areas encompass clinical electroencephalography, epilepsy management, and the application of large language models in medical trials. Recent articles include studies on seizure detection, medication trials, and the use of wearable seizure detectors.

Articles (19)

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Collaborators (9)

Adam Greenblatt

Assistant Professor

Washington University in St. Louis

UNITED STATES

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Benjamin Brinkmann

Professor

Mayo Clinic

UNITED STATES

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Alexander Baumgartner

University of Colorado Boulder

UNITED STATES

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Pedro Viana

King’s College London

UNITED KINGDOM

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Mark Philip Richardson

King’s College London

UNITED KINGDOM

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Fábio Augusto Nascimento e Silva

Assistant Professor of Neurology

Washington University in St. Louis

UNITED STATES

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M. Brandon Westover

UNITED STATES

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Elisa Bruno

King’s College London

UNITED KINGDOM

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Rosalind Picard

Professor

Massachusetts Institute of Technology

UNITED STATES

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Daniel Goldenholz

Research Interests

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About

Articles (19)

Expert-Level Detection of Epilepsy Markers in EEG on Short and Long Timescales

Harvard Electroencephalography Database: A comprehensive clinical electroencephalographic resource from four Boston hospitals

Increased seizure frequency graphs in medication trials: FDA labels vs. peer-review

The Road Not Taken: Misclassifying an Anti‐Seizure Medication as a Failure

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy

Statistical characteristics of large‐scale objective tonic–clonic seizure records from medical smartwatches used in daily life

Minimum clinical utility standards for wearable seizure detectors

How accurate do self‐reported seizures need to be for effective medication management in epilepsy?

Prospective validation of a seizure diary forecasting falls short

Quantifying and controlling the impact of regression to the mean on randomized controlled trials in epilepsy

Can machine learning solve this one? Clinical pitfalls in surgical outcome prediction

Gaps in care following first time seizure in an underserved region: A retrospective analysis

Sample Size Analysis for Machine Learning Clinical Validation Studies

Flexible realistic simulation of seizure occurrence recapitulating statistical properties of seizure diaries

Guidelines for Conducting Ethical Artificial Intelligence Research in Neurology

Recognizing and refuting the myth of tongue swallowing during a seizure

Statistical efficiency of patient data in randomized clinical trials of epilepsy treatments adds value

Development and Validation of Forecasting Next Reported Seizure Using e‐Diaries

Statistical efficiency of patient data in randomized clinical trials of epilepsy treatments

Collaborators (9)

Adam Greenblatt

Benjamin Brinkmann

Alexander Baumgartner

Pedro Viana

Mark Philip Richardson

Fábio Augusto Nascimento e Silva

M. Brandon Westover

Elisa Bruno

Rosalind Picard

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