Search alternatives:
selection algorithm » detection algorithm (Expand Search), detection algorithms (Expand Search)
multimode variable » multi variable (Expand Search), multimode particle (Expand Search)
selection algorithm » detection algorithm (Expand Search), detection algorithms (Expand Search)
multimode variable » multi variable (Expand Search), multimode particle (Expand Search)
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datasheet1_Spatio-Temporal Inversion Using the Selection Kalman Model.zip
Published 2021“…An efficient recursive algorithm for assessing the selection Kalman model is specified. …”
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DataSheet1_Spatio-Temporal Inversion Using the Selection Kalman Model.pdf
Published 2021“…An efficient recursive algorithm for assessing the selection Kalman model is specified. …”
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Image_1_On the Use of a Multimodal Optimizer for Fitting Neuron Models. Application to the Cerebellar Granule Cell.TIF
Published 2021“…We overcome the intrinsic limitations of the extant optimization methods by proposing an alternative optimization component based on multimodal algorithms. This approach can natively explore a diverse population of neuron model configurations. …”
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Table 1_Combinations of multimodal neuroimaging biomarkers and cognitive test scores to identify patients with cognitive impairment.docx
Published 2025“…The structural, perfusion, and diffusion MRI-derived biomarkers remained in the identification model with variable selection with the elastic net algorithm, and were thus considered important variables.…”
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Image1_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.tiff
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table2_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table5_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.docx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table3_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table2_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table5_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.docx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table1_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.docx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table4_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table4_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Image1_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.tiff
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table1_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.docx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Table3_Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.xlsx
Published 2023“…Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting.…”
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Supplementary file 1_Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study.pdf
Published 2025“…Feature selection was performed using Lasso Regression, XGBoost, and Random Forest machine learning algorithms, and a nomogram model was developed using univariate and multivariate Cox regression analyses, with validation of its accuracy, concordance, and clinical applicability.…”
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Image 1_An interpretable machine learning model using multimodal pretreatment features predicts pathological complete response to neoadjuvant immunochemotherapy in esophageal squam...
Published 2025“…</p>Results<p>Following feature selection, 17 variables were incorporated into model construction. …”
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