ArticleChaos (Woodbury, N.Y.)2012
Using time-delayed mutual information to discover and interpret temporal correlation structure in complex populations.
Article in Chaos (Woodbury, N.Y.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03911687 (Communicating Narrative Concerns Entered by RNs), which is not on this map. Cited by 25 papers.
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.
Communicating Narrative Concerns Entered by RNs (CONCERN) Clinical Decision Support (CDS) System
Who cites it
25 citing papers in PubMed.
- A multiobjective optimization approach to data assimilation for complex biological systems with sparse data.Mathematical biosciences · 2026Article
- Developing A Data Pipeline to Quantify Ventilator Waveforms.medRxiv : the preprint server for health sciences · 2025Article
- Probing Asymmetric Interactions with Time-Separated Mutual Information: A Case Study Using Golden Shiners.Entropy (Basel, Switzerland) · 2024Article
- Inferring Dealer Networks in the Foreign Exchange Market Using Conditional Transfer Entropy: Analysis of a Central Bank Announcement.Entropy (Basel, Switzerland) · 2024Article
- Multisite Pragmatic Cluster-Randomized Controlled Trial of the CONCERN Early Warning System.medRxiv : the preprint server for health sciences · 2024Article
- Missing data matter: an empirical evaluation of the impacts of missing EHR data in comparative effectiveness research.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Embedding optimization reveals long-lasting history dependence in neural spiking activity.PLoS computational biology · 2021Article
- Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.Journal of biomedical informatics · 2018Article
- Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.BMJ (Clinical research ed.) · 2018Observational
- High-fidelity phenotyping: richness and freedom from bias.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Yield and bias in defining a cohort study baseline from electronic health record data.Journal of biomedical informatics · 2018Article
- Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.Journal of biomedical informatics · 2018Article
- Identification of Bifurcations from Observations of Noisy Biological Oscillators.Biophysical journal · 2016Article
- Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- WebDISCO: a web service for distributed cox model learning without patient-level data sharing.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Predictability Bounds of Electronic Health Records.Scientific reports · 2015Article
- Parameterizing time in electronic health record studies.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Identifying and mitigating biases in EHR laboratory tests.Journal of biomedical informatics · 2014Article
- Survival Analysis with Electronic Health Record Data: Experiments with Chronic Kidney Disease.Statistical analysis and data mining · 2014Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
This paper addresses how to calculate and interpret the time-delayed mutual information (TDMI) for a complex, diversely and sparsely measured, possibly non-stationary population of time-series of unknown composition and origin. The primary vehicle used for this analysis is a comparison between the time-delayed mutual information averaged over the population and the time-delayed mutual information of an aggregated population (here, aggregation implies the population is conjoined before any statistical estimates are implemented). Through the use of information theoretic tools, a sequence of practically implementable calculations are detailed that allow for the average and aggregate time-delayed mutual information to be interpreted. Moreover, these calculations can also be used to understand the degree of homo or heterogeneity present in the population. To demonstrate that the proposed methods can be used in nearly any situation, the methods are applied and demonstrated on the time series of glucose measurements from two different subpopulations of individuals from the Columbia University Medical Center electronic health record repository, revealing a picture of the composition of the population as well as physiological features.
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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.