Showing 5 ideas for tag "informatics"
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Transformative Research Priorities for the Epilepsies

Multicenter networks to foster transformative clinical research

We advocate for a deliberate investment in collaborative, national or international efforts to rapidly and rigorously collect and share clinical data on patients with epilepsy, particularly those with rare genetic variants. Development of an infrastructure of clinical informatics tools that can plug into a national or international network for epilepsy centers could transform the field. A learning healthcare system model... more »

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(@gerryn) kudos icon 9

2020 Epilepsy Research Benchmarks

Merge and share datasets across different research studies

Epilepsy patients' research data are typically collected and stored in standalone de-identified database silos, making it impossible to merge or compare data across disparate research studies or give feedback to the patient. A patient-generated clinical research ID (CRID) could be used to merge and share data across different research studies for the same patient without revealing PHI/PII data. CRID enables a secure two-way... more »

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(@jayetta) kudos icon 17

Transformative Research Priorities for the Epilepsies

Laying the Foundation for an Epilepsy Moonshot

More substantive research priorities, however well framed and targeted, can not alone overcome the inefficiencies and silo-ed structure for clinical care and research in the epilepsies.

By integrating clinical care and research—the standard for decades in pediatric oncology—we will get on a path where we will start seeing improvements in the quality of life for all those living with and too often dying from epilepsy.... more »

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(@gerryn) kudos icon 5

2020 Epilepsy Research Benchmarks

Epilepsy-related "training" datasets for machine learning

Most epilepsy-related Machine Learning (ML) tools tend to focus on seizure detection using readily available EEG "training" datasets. ML has potentially many other epilepsy-related use cases beyond seizure detection that are yet to be discovered, but the lack of "training" data is likely hindering its use. If tools could be developed to help identify and generate new "training" data from existing epilepsy datasets, ML... more »

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