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Showing 1 - 6 results of 6 for search '(( binary values given optimization algorithm ) OR ( binary values led optimization algorithm ))', query time: 0.45s Refine Results
  1. 1
    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes

    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

    Published 2022
    “…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
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  2. 2
    Experimental observation of gastruloids and shape quantification using LOCO-EFA.

    Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

    Published 2024
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  3. 3
    Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabetes model.

    Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... by Ramsés Noguez Imm (6658637)

    Published 2023
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  4. 4
    Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports

    Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports by Olivier Q. Groot (9370461)

    Published 2020
    “…At the same threshold, the NLP algorithm had a positive predictive value of 0.97 and F1-score of 0.96.…”
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  5. 5
    Seed mix selection model

    Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

    Published 2022
    “…</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
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  6. 6
    Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX

    Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX by Orit Mazza (12081914)

    Published 2022
    “…Decision trees were constructed by a hierarchical binary recursive partitioning algorithm to predict the BP-lowering of 10–30% off the maximal value when antihypertensive treatment was given in patients with an extremely high BP (above 220/110 or 180/105 mmHg for patients receiving thrombolysis), according to the American Heart Association/American Stroke Association (AHA/ASA), the European Society of Cardiology, and the European Society of Hypertension (ESC/ESH) guidelines. …”
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