ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2014
MEDCIS: Multi-Modality Epilepsy Data Capture and Integration System.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Transforming epilepsy research: A systematic review on natural language processing applications.Epilepsia · 2023Pooled it
- Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.Journal of biomedical informatics · 2017Pooled it
- Leveraging pretrained language models for seizure frequency extraction from epilepsy evaluation reports.NPJ digital medicine · 2025Article
- Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application.BMC medical informatics and decision making · 2024Article
- An Interactive Information Visualization System for Temporal Queries in a Large-scale COVID-19 EHR Dataset (COVID-SPHERE): development and qualitative evaluation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Extracting Temporal Expressions of First Seizure Onset from Epilepsy Patient Discharge Summaries.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- The analysis of SUDEP forensic autopsies leading to preventable events.Frontiers in neurology · 2023Article
- A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy.Frontiers in big data · 2022Article
- Temporal Cohort Logic.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- ELII: A novel inverted index for fast temporal query, with application to a large Covid-19 EHR dataset.Journal of biomedical informatics · 2021Article
- A Bespoke Electronic Health Record for Epilepsy Care (EpiToMe): Development and Qualitative Evaluation.Journal of medical Internet research · 2021Article
- Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry.BMC medical informatics and decision making · 2020Article
- Big data in status epilepticus.Epilepsy & behavior : E&B · 2019Review
- The National Sleep Research Resource: towards a sleep data commons.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Regional cortical thickness changes accompanying generalized tonic-clonic seizures.NeuroImage. Clinical · 2018Article
- Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- ODaCCI: Ontology-guided Data Curation for Multisite Clinical Research Data Integration in the NINDS Center for SUDEP Research.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- The Pre-Eclampsia Ontology: A Disease Ontology Representing the Domain Knowledge Specific to Pre-Eclampsia.PloS one · 2016Article
- FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies.BioData mining · 2016Article
- NHash: Randomized N-Gram Hashing for Distributed Generation of Validatable Unique Study Identifiers in Multicenter Research.JMIR medical informatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Sudden Unexpected Death in Epilepsy (SUDEP) is the leading mode of epilepsy-related death and is most common in patients with intractable, frequent, and continuing seizures. A statistically significant cohort of patients for SUDEP study requires meticulous, prospective follow up of a large population that is at an elevated risk, best represented by the Epilepsy Monitoring Unit (EMU) patient population. Multiple EMUs need to collaborate, share data for building a larger cohort of potential SUDEP patient using a state-of-the-art informatics infrastructure. To address the challenges of data integration and data access from multiple EMUs, we developed the Multi-Modality Epilepsy Data Capture and Integration System (MEDCIS) that combines retrospective clinical free text processing using NLP, prospective structured data capture using an ontology-driven interface, interfaces for cohort search and signal visualization, all in a single integrated environment. A dedicated Epilepsy and Seizure Ontology (EpSO) has been used to streamline the user interfaces, enhance its usability, and enable mappings across distributed databases so that federated queries can be executed. MEDCIS contained 936 patient data sets from the EMUs of University Hospitals Case Medical Center (UH CMC) in Cleveland and Northwestern Memorial Hospital (NMH) in Chicago. Patients from UH CMC and NMH were stored in different databases and then federated through MEDCIS using EpSO and our mapping module. More than 77GB of multi-modal signal data were processed using the Cloudwave pipeline and made available for rendering through the web-interface. About 74% of the 40 open clinical questions of interest were answerable accurately using the EpSO-driven VISual AGregagator and Explorer (VISAGE) interface. Questions not directly answerable were either due to their inherent computational complexity, the unavailability of primary information, or the scope of concept that has been formulated in the existing EpSO terminology system.
Indexed as
Identifiers
25954436PMC4420009What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.