Search alternatives:
based optimization » whale optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary basic » binary mask (Expand Search)
primary aim » primary care (Expand Search), primary data (Expand Search)
basic codon » basic column (Expand Search)
aim based » ai based (Expand Search), bim based (Expand Search), aom based (Expand Search)
based optimization » whale optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
binary basic » binary mask (Expand Search)
primary aim » primary care (Expand Search), primary data (Expand Search)
basic codon » basic column (Expand Search)
aim based » ai based (Expand Search), bim based (Expand Search), aom based (Expand Search)
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The duration of a single cycle, measured in ms.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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GBO framework used to estimate the battery SOH.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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#EV PDF (drive cycle durations).
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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27
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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28
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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29
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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30
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX
Published 2023“…<p>Background: Almost all patients treated with androgen deprivation therapy (ADT) eventually develop castration-resistant prostate cancer (CRPC). Our research aims to elucidate the potential biomarkers and molecular mechanisms that underlie the transformation of primary prostate cancer into CRPC.…”
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Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX
Published 2023“…<p>Background: Almost all patients treated with androgen deprivation therapy (ADT) eventually develop castration-resistant prostate cancer (CRPC). Our research aims to elucidate the potential biomarkers and molecular mechanisms that underlie the transformation of primary prostate cancer into CRPC.…”
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Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX
Published 2023“…<p>Background: Almost all patients treated with androgen deprivation therapy (ADT) eventually develop castration-resistant prostate cancer (CRPC). Our research aims to elucidate the potential biomarkers and molecular mechanisms that underlie the transformation of primary prostate cancer into CRPC.…”
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Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx
Published 2021“…<p>Background and Purpose: Treatment for mild stroke remains an open question. We aim to develop a decision support tool based on machine learning (ML) algorithms, called DAMS (Disability After Mild Stroke), to identify mild stroke patients who would be at high risk of post-stroke disability (PSD) if they only received medical therapy and, more importantly, to aid neurologists in making individual clinical decisions in emergency contexts.…”
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Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx
Published 2021“…<p>Background and Purpose: Treatment for mild stroke remains an open question. We aim to develop a decision support tool based on machine learning (ML) algorithms, called DAMS (Disability After Mild Stroke), to identify mild stroke patients who would be at high risk of post-stroke disability (PSD) if they only received medical therapy and, more importantly, to aid neurologists in making individual clinical decisions in emergency contexts.…”
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Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx
Published 2025“…Finally, an online predictive tool based on the optimal model was developed to provide real-time individualized VTE risk predictions for PMN patients.…”
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