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access optimization » process optimization (Expand Search), stress optimization (Expand Search), process optimisation (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
binary data » dietary data (Expand Search)
data access » data across (Expand Search), water access (Expand Search)
data based » data used (Expand Search)
access optimization » process optimization (Expand Search), stress optimization (Expand Search), process optimisation (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
binary data » dietary data (Expand Search)
data access » data across (Expand Search), water access (Expand Search)
data based » data used (Expand Search)
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Furthermore, it reflects strong potentialities to develop data-driven individualized chemotherapy treatments in the future.…”
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Furthermore, it reflects strong potentialities to develop data-driven individualized chemotherapy treatments in the future.…”
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Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change"
Published 2025“…The process includes (1) harmonizing Landsat 5, 7, 8, and Sentinel-2 data using the HLS algorithm, and (2) filling temporal gaps with an optimized object-based STARFM fusion algorithm. …”
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Confusion matrix for multiclass classification.
Published 2025“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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General flow chart of the proposed method.
Published 2025“…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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Image 2_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png
Published 2024“…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…”
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Image 1_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png
Published 2024“…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…”
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primary mouse RT single cell RNA-seq
Published 2023“…The clustering was conducted using the graph-based modularity optimization Louvain algorithm implemented in Seurat v3. …”
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Results of Comprehensive weighting.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”
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The prediction error of each model.
Published 2025“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”