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  1. 2201
    “…Tools were tested in a controlled genomic scenario, representing the ground-truth and allowing us to determine software performance.…”
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    Exploration of Tools for the Interpretation of Human Non-Coding Variants
  2. 2202
    “…The synthesis of honeycomb patterns on ordinary images allows conveniently learning and validating the network without the enormous ground truth collection by extra hardware setups. As a result, HAR-CNN shows significant performance improvement in honeycomb pattern removal and also detailed preservation for the 1961 USAF chart sample, compared with other conventional methods. …”
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    Honeycomb Artifact Removal Using Convolutional Neural Network for Fiber Bundle Imaging
  3. 2203
    “…We demonstrate this using an optically trapped spherical particle for which we obtain an analytical solution to use as ground truth. Then, we take advantage of the acceleration provided by neural networks to study the dynamics of ellipsoidal particles in a double trap, which would be computationally impossible otherwise.…”
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    Faster and More Accurate Geometrical-Optics Optical Force Calculation Using Neural Networks
  4. 2204
    por Wertgen, Andreas G., Richter, Tobias
    Publicado 2023
    “…These general knowledge questions can be used in studies with German speaking participants in a broad range of research fields, such as memory, illusory truth, misinformation, and metacognitive processes.…”
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    General knowledge norms: Updated and expanded for German
  5. 2205
    “…The difference between the reconstructions and the simulation ground truth is calculated by the ℓ(2)-norm image difference. …”
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    Structural priors represented by discrete cosine transform improve EIT functional imaging
  6. 2206
    “…Each wound had a ground truth determined by a consensus panel of study investigators using still photograph at 21-days post-injury to discern healing and non-healing regions. …”
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    47 Burn Injury Assessment Study (BIAS): Is There Room To Improve?
  7. 2207
    “…Conclusion: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.…”
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    Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
  8. 2208
    por Ji, Zhengran, Hu, Mike, Xin, Huolin L.
    Publicado 2023
    “…To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. …”
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    MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration
  9. 2209
    “…The accuracy of KL grading was 0.83, and the kappa coefficient between the AI model and ground truth was 0.768, which demonstrated substantial consistency. …”
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    Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis
  10. 2210
    “…In the visually assessed validation data sets, the ground truth step count was 367.4 (SD 359.4) steps, while the mean bias was –0.4 (LoA –75.2, 74.3) steps, or 0.1%. …”
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    Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study
  11. 2211
    “…We also performed a qualitative visual similarity assessment between the synthetic and ground‐truth images. The effectiveness of the proposed model was compared with a 3D U‐Net baseline model and existing deep learning‐based methods in the literature. …”
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    Contrast‐enhanced MRI synthesis using dense‐dilated residual convolutions based 3D network toward elimination of gadolinium in neuro‐oncology
  12. 2212
    “…RESULTS: A significantly high correlation of R(2) = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. …”
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    Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat
  13. 2213
    “…MAIN OUTCOMES AND MEASURES: Area under the curve, Dice score coefficient (DSC) (a metric from 0-1 indicating the extent of overlap between the prediction and the ground truth; a DSC of ≥0.5 represents significant overlap), and volume error. …”
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    Use of Deep Learning to Predict Final Ischemic Stroke Lesions From Initial Magnetic Resonance Imaging
  14. 2214
    “…We train our neural model in a self-supervised fashion using ground truth drug side effects from mayoclinic.org. NEAT learns to assign each user a score that is descriptive of their credibility and highlights the critical textual segments of their post. …”
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    Neural side effect discovery from user credibility and experience-assessed online health discussions
  15. 2215
    “…The DLA showed varied performance according to the different methods of ground truth.…”
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    Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort
  16. 2216
    “…To avoid unreliable manual delineations, the ground truth was generated with a semi-automated approach: a volume containing the tumor and excluding the bladder was first manually determined, then a well-validated, semi-automated approach relying on the Fuzzy locally Adaptive Bayesian (FLAB) algorithm was applied to generate the ground truth. …”
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    Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting
  17. 2217
    “…Principal strain maps of Monte Carlo tMRI simulations with various anatomical, functional, and imaging parameters demonstrate artifact-free solid agreements with the corresponding ground-truth maps. Correlations with the ground-truth strain maps were R = 0.90 and 0.92 for the best-proposed cGAN approach compared to R = 0.12 and 0.73 for the best HARP method for [Formula: see text] and [Formula: see text] , respectively. …”
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    Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain)
  18. 2218
    “…Results were compared to the corresponding ground truth using the Dice similarity coefficient (DSC), Spearman’s correlation coefficient and Wilcoxon signed-rank test. …”
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    Automated major psoas muscle volumetry in computed tomography using machine learning algorithms
  19. 2219
    “…Image similarity was evaluated between syn-MRI and the ground truth using a 4-grade visual rating scale, the peak signal-to-noise ratio (PSNR), and the structural similarity index measure (SSIM). …”
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    Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks
  20. 2220
    “…Most participants identified the following major end-of-life care preferences: having loved ones around (98.1%), being free from distressing symptoms (95.8%), receiving the full truth (95.0%), and having meaning in their lives (95.0%). …”
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    General population-based study on preferences towards end-of-life care in Southern Thailand: a cross-sectional survey
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