This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file. and Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/ejhy-5h41
The research adheres to PRISMA-HARM recommendations for systematic reviews. The reproducible search strategies for all databases, the citation export files from all databases, and the eligibility screening decisions are included in the dataset.
The search data supports a literature review project on lifestyle therapies for the management of atrial fibrillation. The data included in the dataset are the reproducible search strategies (in docx) and the exported results of all citations from all databases (txt and ris files). These searches and exported result files contain all citations originating from the database searches that were considered for inclusion.
Three sensitivity analyses were performed. First, a second matching step was performed in which two controls were selected for each case, where possible using a nearest neighbor and caliper metric. Controls needed to have propensity scores within 0.1 of the case to be selected. Thirty-eight of the 39 cases had at least one control using this method and for 36 cases two controls could be selected. The average difference between case and control propensity adjuvant RT was 0.008 (range 0.00003-0.095).
A second sensitivity analysis was performed to guard against immortal time bias. In order to mitigate the possibility of this effect, cases known not to have undergone adjuvant RT have been screened for suitable follow-up without a recurrence (local or regional recurrence, metastatic failure, and/or death) to ensure that if adjuvant RT had been prescribed as part of the multi-modality treatment regimen, that it would have been initiated. Three months was selected as the mandatory follow-up time. One to one matching was carried out and all 39 cases were matched to a control. A third sensitivity analysis was performed to account for stage migration seen in control patients that presented to the University of Michigan with more advanced disease. Patients that underwent adjuvant radiation were matched one to one with control group patients who did not receive adjuvant radiation, and who had the same stage at diagnosis as compared to stage at University of Michigan presentation.
Data include variables used to run accelerated failure time models examining the association between the nose/throat microbiome and 1) symptom duration, 2) shedding duration, and 3) time to infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications.
Data include variables used to run mixed effects models examining the association between the nose/throat microbiome and influenza virus infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications. and Curation Notes: Readme updated Nov. 29, 2018 with context for oligotype and taxonomy files, and citation to associated article.
Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal.
The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.