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939 results for “Validation studies”
Data from: Biomarker detection and validation for corneal involvement in patients with acute infectious conjunctivitis: A multi-country study
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Development and validation of the Health Belief Model questionnaire to promote smoking cessation for nasopharyngeal cancer prevention: a cross-sectional study
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Monitoring mobility in older adults using a global positioning system (GPS) smartwatch and accelerometer: A validation study
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Data from: cross-validation matters in species distribution models: a case study with goatfish species
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Data from: Validating marine Devonian biogeography: a study in bioregionalization
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A cross sectional study on adaptation and initial validation of a test to evaluate health claims among high school students – Croatian version
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Data from: Development of a sustainability assessment algorithm and its validation using case studies on cryogenic machining
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Raw data on Validation Study of the Revised Spirituality and Spiritual Care Rating Scale (SSCRS): A Cross-Sectional Survey in Poland
<p>Raw data on Validation Study of the Revised Spirituality and Spiritual Care Rating Scale (SSCRS): A Cross-Sectional Survey in Poland.</p>
Supporting Information for "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies"
<p>This contains data sets and their description for the paper "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies" submitted to the journal Earth and Space Science by this author. This study investigates the uncertainty introduced into comparisons (between e.g. AERONET ground observations, satellite retrievals, or model simulations) of aerosol optical properties due to differences in time of observation between the data sets. This uncertainty source has historically been neglected but is potentially important in some situations.</p> <p> </p> <p>Journal policies are that Supporting Information data sets can no longer be archived with the paper, but instead should be uploaded to a separate repository. As a result, I have uploaded these data here.</p> <p> </p> <p>This data set consists of one pdf file describing the data sets, and then two zip archives containing the data (ASCII format). The total size is approximately 10 MB. These data files allow the reproduction of analysis results in this paper, and enable researchers to estimate temporal mismatch uncertainties in their own analyses involving AERONET sites.</p>
Data from: A from-benchtop-to-desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies
The main objective of this work was to develop and validate a robust and reliable 'from benchtop-to-desktop' metabarcoding workflow to investigate the diet of invertebrate-eaters. We applied our workflow to fecal DNA samples of an invertebrate-eating fish species. A fragment of the COI gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of non-arbitrary thresholds established from control samples and from molecular replicates in order to address the elimination of cross-contamination, PCR/sequencing errors and mistagging artifacts. This resulted in a conservative and informative metabarcoding dataset. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semi-quantitative statistic in our diet study, the Minimum Number of Individuals (MNI), which is based on the number of distinct variants in each sample. The metabarcoding approach described in this paper may guide future diet studies that aim to produce robust datasets associated with a fine and accurate identification of prey items.
Development and validation of a postoperative delirium prediction model for patients admitted to an intensive care unit in China: a prospective study
<p>Objectives: We aimed to develop <span class="il">and</span> validate <span class="il">a</span> <span class="il">postoperative</span> <span class="il">delirium</span> (POD) <span class="il">prediction</span> model for patients admitted to the intensive care unit (ICU).</p> <p>Design: <span class="il">A</span> prospective study was conducted.</p> <p>Setting: The study was conducted in the surgical, cardiovascular surgical, <span class="il">and</span> trauma surgical ICUs <span class="il">of</span> an affiliated hospital <span class="il">of</span> <span class="il">a</span> medical university in Heilongjiang Province, China.</p> <p>Participants: This study included 400 patients (≥18 years old) admitted to the ICU after surgery.</p> <p>Primary <span class="il">and</span> secondary outcome measures: The primary outcome measure was <span class="il">postoperative</span> <span class="il">delirium</span> assessment during ICU stay.</p> <p>Results: The model was developed using 300 consecutive ICU patients <span class="il">and</span> was validated using 100 patients from the same ICUs. The model was based on five risk factors: Physiological <span class="il">and</span> Operative Severity Score for the Enumeration <span class="il">of</span> Mortality <span class="il">and</span> Morbidity; acid-base disturbance; <span class="il">and</span> history <span class="il">of</span> coma, diabetes, or hypertension. The model had an area under the receiver operating characteristics curve <span class="il">of</span> 0.852 (95% confidence interval: 0.802–0.902), Youden index <span class="il">of</span> 0.5789, sensitivity <span class="il">of</span> 70.73%, <span class="il">and</span> specificity <span class="il">of</span> 87.16%. The Hosmer-Lemeshow goodness <span class="il">of</span> fit was 5.203 (P = 0.736). At <span class="il">a</span> cut-off <span class="il">of</span> 24.5%, the sensitivity <span class="il">and</span> specificity were 71% <span class="il">and</span> 69%, respectively.</p> <p>Conclusions: The model, which used readily available data, exhibited high predictive value regarding risk <span class="il">of</span> intensive care unit <span class="il">postoperative</span> <span class="il">delirium</span> (ICU-POD) at admission. Use <span class="il">of</span> this model may facilitate better implementation <span class="il">of</span> preventive treatments <span class="il">and</span> nursing measures.</p>
Data from: Validation of the hospital frailty risk score in a tertiary care hospital in Switzerland: results of a prospective, observational study
Objectives: Recently, the Hospital Frailty Risk Score based on a derivation and validation study in the United Kingdom has been proposed as a low-cost, systematic screening tool to identify older, frail patients who are at greater risk of adverse outcomes and for whom a frailty-attuned approach might be useful. We aimed to validate this Score in an independent cohort in Switzerland. Design: Secondary analysis of a prospective, observational study (TRIAGE study). Setting: One 600-bed tertiary care hospital in Aarau, Switzerland Participants: Consecutive medical inpatients aged 75 years or older that presented to the emergency department or were electively admitted between October 2015 and April 2018. Primary and secondary outcome measures: The primary endpoint was all-cause 30-day mortality. Secondary endpoints were length of hospital stay, hospital readmission, functional impairment, and quality of life measures. We used multivariate regression analyses. Results: Of 4957 included patients, 3150 (63.5%) were classified as low risk, 1663 (33.5%) intermediate risk, and 144 (2.9%) high risk for frailty. Compared to the low-risk group, patients in the moderate risk and high-risk groups had increased risk for 30-day mortality (odds ratio [OR] 2.53, 95%CI 2.09 to 3.06, P<0.001 and OR 4.40, 95%CI 2.94 to 6.57, P<0.001) with overall moderate discrimination (area under the ROC curve 0.66). The results remained robust after adjustment for important confounders. Similarly, we found longer length of hospital stay, more severe functional impairment and a lower quality of life in higher risk group patients. Conclusion: Our data confirms the prognostic value of the Hospital Frailty Risk Score to identify older, frail people at risk for mortality and adverse outcomes in an independent patient population. Trial registration number: ClinicalTrials.gov; Identifier: NCT01768494
FIGURES 14–15 in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 14–15. Discheramocephalus adults, posterior margin of the head. 14. D.interfusus x 1020; 15. D. parvus x 930. FIGURES 16–17. Discheramocephalus adults, meso- and metaventrites. 16 D. capac; 17. D. angustus. FIGURES 18–19. Discheramocephalus adults, abdominal ventrites showing pits on ventrite VIII. 18. D. capac 19. D. angustus.
FIGURES 25–30. Discheramocephalus adults. Mesosternal collar and keel. 25. D. malalae x 1340 in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 25–30. Discheramocephalus adults. Mesosternal collar and keel. 25. D. malalae x 1340; 26. D. interfusus x1120; 27. D. capac x 990; 28. D. inretitus x 1200; 29. D. parvus x 1400; 30. D. angustus x 1120.
FIGURES 31–32. Discheramocephalus adults. First visible abdominal ventrite 31. D. malalae x 2140 in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 31–32. Discheramocephalus adults. First visible abdominal ventrite 31. D. malalae x 2140; 32. D. angustus x 2060. FIGURE 33. Adult D. inretitus abdominal ventrites x 760 to show medial serrations.
FIGURES 8–13. Discheramocephalus adults, pronota. 8. D. malalae x 695 in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 8–13. Discheramocephalus adults, pronota. 8. D. malalae x 695; 9. D. capac x 645; 10. D. interfusus x 695; 11. D. inretitus x 655; 12. D. parvus x 725; 13. D. angustus x 660.
FIGURES 2–7. Discheramocephalus adults, dorsal habitus. 2. D in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 2–7. Discheramocephalus adults, dorsal habitus. 2. D. malalae; 3. D. capac; 4. D. interfusus; 5. D.inretitus; 6. D. parvus; 7. D. angustus.
FIGURES 20–24 in Studies of Peruvian Ptiliidae (Coleoptera) 3: the genus Discheramocephalus Johnson including six new species, and validation of the unavailable generic name Phytotelmatrichis Darby and Chaboo
FIGURES 20–24. Discheramocephalus adults, mouthparts. Mentum and submentum. 20. D. malalae x 1340; 21. D. capac x 1440; 22. D.inretitus x 1200; 23. D. parvus x 730; 24. D. angustus x 610.
Genotyping validates the efficacy of photographic identification in a capture-mark-recapture study based on the head scale patterns of the prairie lizard (Sceloporus consobrinus)
Population studies often incorporate capture-mark-recapture (CMR) techniques to gather information on long-term biological and demographic characteristics. A fundamental requirement for CMR studies is that an individual must be uniquely and permanently marked to ensure reliable reidentification throughout its lifespan. Photographic identification involving automated photographic identification software has become a popular and efficient non-invasive method for identifying individuals based on natural markings. However, few studies have a) robustly assessed the performance of automated programs by using a double-marking system or b) determined their efficacy for long-term studies by incorporating multi-year data. Here, we evaluated the performance of the program Interactive Individual Identification System (I<sup>3</sup>S) by cross-validating photographic identifications based on the head scale pattern of the prairie lizard (<i>Sceloporus consobrinus</i>) with individual microsatellite genotyping (N=863). Further, we assessed the efficacy of the program to identify individuals over time by comparing error rates between within-year and between-year recaptures. Recaptured lizards were correctly identified by I<sup>3</sup>S in 94.1% of cases. We estimated a false rejection rate (FRR) of 5.9% and a false acceptance rate (FAR) of 0%. By using I<sup>3</sup>S we correctly identified 97.8% of within-year recaptures (FRR=2.2%; FAR=0%) and 91.1% of between-year recaptures (FRR=8.9%; FAR=0%). Misidentifications were primarily due to poor photo quality (N=4). However, two misidentifications were caused by indistinct scale configuration due to scale damage (N=1) and ontogenetic changes in head scalation between capture events (N=1). We conclude that automated photographic identification based on head scale patterns is a reliable and accurate method for identifying individuals over time. Because many lizard or reptilian species possess variable head squamation, this method has potential for successful application in many species.
Dataset of the study "Factor Structure, Validity, and Reliability of the STarT Back Screening Tool in Italian Obese and Non-obese Patients With Low Back Pain"
<p>Dataset of the study "Factor Structure, Validity, and Reliability of the STarT Back Screening Tool in Italian Obese and Non-obese Patients With Low Back Pain" published in Frontiers in Psychology 20 October 2021 12:740851, doi: 10.3389/fpsyg.2021.740851</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.