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  1. 5661
    “…Image reconstruction results were compared to ground truth data in the k-f domain by means of modulation transfer function (MTF) analysis. …”
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    Analysis of spatiotemporal fidelity in quantitative 3D first-pass perfusion cardiovascular magnetic resonance
  2. 5662
    “…Exploiting an ITV-based treatment planning approach, VMAT treatment plans were generated for a motion phantom and different motion scenarios (sinusoidal motion of different period/direction; regular/irregular motion). 4D VMAT dose simulation results and dose measurements were compared by local 3% / 3 mm γ-evaluation, with the measured dose distributions serving as ground truth. Overall γ-passing rates of simulations and dynamic measurements ranged from 97% to 100% (mean across all motion scenarios: 98% ± 1%); corresponding values for comparison of different day repeat measurements were between 98% and 100%. …”
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    4D dose simulation in volumetric arc therapy: Accuracy and affecting parameters
  3. 5663
    “…We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300 mT/m and a broad set of diffusion times. …”
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    Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi‐group comparison
  4. 5664
    “…However, the role of this hormone is highly controversial as certain studies suggest it has anti-tumor properties while others have found it to be pro-tumorigenic. To unveil the truth, we have analyzed the expression of β-hCG in breast cancer. …”
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    BRCA1 regulation on β-hCG: a mechanism for tumorigenicity in BRCA1 defective breast cancer
  5. 5665
    “…Validity of knowledge appears not to be based on criteria of consensus, coherence, or correspondence but on a more polyphonic understanding of truth. We contend that our findings give enough ground for further research on how exploring mindlines of clinicians online could help improve guideline development processes.…”
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    How Knowledge Is Constructed and Exchanged in Virtual Communities of Physicians: Qualitative Study of Mindlines Online
  6. 5666
    “…River network data obtained from either digitised maps or derived from 30 m resolution digital elevation model (DEM) data as a proxy for ground truth data. Other environmental variables were derived from publicly-available resolution remotely sensed data (e.g. …”
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    The development of high resolution maps of tsetse abundance to guide interventions against human African trypanosomiasis in northern Uganda
  7. 5667
    “…Using data from the 2011–2015 National Youth Tobacco Survey (NYTS) and corresponding years of the Truth Initiative Young Adult Cohort Study (TIYAC), past 30-day use of the following products was assessed: cigarettes, e-cigarettes, any type of cigar, smokeless tobacco, hookah, and other tobacco products (pipe, bidis, kreteks, dissolvable tobacco, and snus). …”
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    Patterns of Nicotine and Tobacco Product Use in Youth and Young Adults in the United States, 2011–2015
  8. 5668
    “…RESULTS: Our automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86). Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. …”
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    Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome
  9. 5669
    “…Manual segmentation was used as ground truth. Dice Scores (DS) were calculated for validation of semiautomatic method. …”
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    Findings of DTI-p maps in comparison with T(2)/T(2)-FLAIR to assess postoperative hyper-signal abnormal regions in patients with glioblastoma
  10. 5670
    “…Our study utilized 85 prostate cancer T2w MRI datasets acquired from across 3 different institutions (1 for discovery, 2 for independent validation), from patients who later underwent radical prostatectomy. Surrogate ground truth for disease extent on MRI was established by expert annotation of pre-operative MRI through spatial correlation with corresponding ex vivo whole-mount histology sections. …”
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    Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study
  11. 5671
    “…In this study, we tested whether literature derived functional cohesion could be used as an objective metric in lieu of ‘ground truth’ to evaluate the quality of probes and microarray datasets. …”
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    Evaluation of Sirtuin-3 probe quality and co-expressed genes using literature cohesion
  12. 5672
    “…Ten standard labels in the procedure and 14 instruments used during surgery were manually annotated, which served as the ground truth. EXPOSURES: Five algorithms with different input data: (1) a support vector machine input with cross-sectional instrument label data; (2) a recurrent neural network (RNN) input with a time series of instrument labels; (3) a convolutional neural network (CNN) input with cross-sectional image data; (4) a CNN-RNN input with a time series of images; and (5) a CNN-RNN input with time series of images and instrument labels. …”
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    Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques
  13. 5673
    “…CONCLUSIONS: Despite the inherent difficulties of determining “truth” in assigning cause of death, these findings suggest that the InterVA-5 model performs well and succeeds in harmonising across a range of input formats. …”
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    An integrated approach to processing WHO-2016 verbal autopsy data: the InterVA-5 model
  14. 5674
    “…Enhancement measured using TUE images was considered the ground truth in this study. For simulation of nonenhancing renal lesions, enhancement values were not significantly different when using VUE versus TUE images, with posterior probabilities ranging from 0.23‐0.56 across all phantom sizes and an associated specificity of 100%. …”
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    Comparison of enhancement quantification from virtual unenhanced images to true unenhanced images in multiphase renal Dual‐Energy computed tomography: A phantom study
  15. 5675
    “…RESULTS: Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. …”
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    Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel
  16. 5676
    “…FIELD STRENGTH/SEQUENCE ASSESSMENT: First, a ground truth signal evolution was simulated from a single‐T(2)* water–fat model. …”
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    Differentiating supraclavicular from gluteal adipose tissue based on simultaneous PDFF and T(2)* mapping using a 20‐echo gradient‐echo acquisition
  17. 5677
    “…By using the sleep stage labels from the LTV EEG as ground truth, an automatic sleep stage classifier based on 30 descriptive features computed from the subcutaneous EEG was trained and tested. …”
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    Automatic sleep stage classification based on subcutaneous EEG in patients with epilepsy
  18. 5678
    “…The availability of count data simulators is extremely valuable both for methods developers, for which a ground truth for tools validation is needed, and for users who want to assess state of the art analysis tools for choosing the most accurate one. …”
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    metaSPARSim: a 16S rRNA gene sequencing count data simulator
  19. 5679
    “…METHODS: Latent class analyses were conducted using four items on nicotine beliefs asked of 4037 adults aged 18–40 in wave 9 (February–March 2016) of the Truth Initiative Young Adult Cohort Study. Confirmatory factor analyses identified three factors from 12 items: nicotine susceptibility (NSUS), nicotine severity (NSEV), and tobacco severity (TSEV). …”
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    Latent Classes of Nicotine Beliefs Correlate with Perceived Susceptibility and Severity of Nicotine and Tobacco Products in US Young Adults
  20. 5680
    “…The 3D map was correlated with ground truth, which was manually determined, pruning the remaining weight. …”
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    On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System
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