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  1. 3281
    Advances in Amazonian Peatland Discrimination With Multi-Temporal PALSAR Refines Estimates of Peatland Distribution, C Stocks and Deforestation
    “...) and optical remote sensing in a machine learning classifier. The new map produced has 95% overall accuracy...”
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  2. 3282
    Quantitative nuclear phenotype signatures predict nodal disease in oral squamous cell carcinoma
    “...-treatment and under-treatment. We present a machine-learning-based model using the quantitative nuclear...”
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  3. 3283
    Plasma-Derived Extracellular Vesicles Circular RNAs Serve as Biomarkers for Breast Cancer Diagnosis
    “... on their circRNA expression profiles of plasma EVs by using multiple machine learning models. By comparing...”
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  4. 3284
    Soil carbon-food synergy: sizable contributions of small-scale farmers
    “... We applied random forest machine learning models to global gridded datasets on crop yield (wheat...”
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  5. 3285
    A Novel Method for Quantitative Analysis of C-Reactive Protein Lateral Flow Immunoassays Images via CMOS Sensor and Recurrent Neural Networks
    “.... <bold>Results:</bold> For the classification of hsCRP, the LSTM outperformed the traditional machine...”
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  6. 3286
    Hollow-tree super: A directional and scalable approach for feature importance in boosted tree models.
    “...<h4>Purpose</h4>Current limitations in methodologies used throughout machine-learning...”
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  7. 3287
    A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.
    “... propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH...”
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  8. 3288
    Artificial intelligence applications in social media for depression screening: A systematic review protocol for content validity processes.
    “... outcome in social media material. We will examine the computational methods, including AI and machine...”
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  9. 3289
    Multiparametric MRI for the improved diagnostic accuracy of Alzheimer's disease and mild cognitive impairment: Research protocol of a case-control study design.
    “... clinics and select classifiers for machine learning that may aid in the disease identification...”
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  10. 3290
    CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.
    “... expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods...”
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  11. 3291
    ADAGE-Based Integration of Publicly Available <named-content content-type="genus-species">Pseudomonas aeruginosa</named-content> Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions
    “... and biological interpretation of these data. We present an unsupervised machine learning approach, ADAGE...”
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  12. 3292
    Meta-analysis of 16S rRNA Microbial Data Identified Distinctive and Predictive Microbiota Dysbiosis in Colorectal Carcinoma Adjacent Tissue
    “... characterization of CRC was underrepresented. Here, considering each taxon as a feature, we demonstrate a machine...”
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  13. 3293
    <named-content content-type="genus-species">Cutibacterium acnes</named-content> (<named-content content-type="genus-species">Propionibacterium acnes</named-content>) 16S rRNA Genotyping of Microbial Samples from Possessions Contributes to Owner Identification
    “... specific. Owner identification accuracy of around 90% based on random forest machine learning was achieved...”
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  14. 3294
    Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set
    “... fields, machine learning (ML) has been shown to successfully create models to predict multiple end points...”
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  15. 3295
    A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease
    “... machine learning models, while disregarding their explainability. As a result, physicians struggle...”
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  16. 3296
    Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification
    “... plaque tissue characterization (PTC) methods were machine learning (ML)-based, which used hand-crafted...”
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  17. 3297
    Multidrug Intrinsic Resistance Factors in <named-content content-type="genus-species">Staphylococcus aureus</named-content> Identified by Profiling Fitness within High-Diversity Transposon Libraries
    “..., as important in limiting the effectiveness of multiple antibiotics. Machine learning identified similarities...”
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  18. 3298
    Artificial intelligence applications in social media for depression screening: A systematic review protocol for content validity processes
    “... outcome in social media material. We will examine the computational methods, including AI and machine...”
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  19. 3299
    A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study
    “... propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH...”
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  20. 3300
    Semi-supervised prediction of SH2-peptide interactions from imbalanced high-throughput data.
    “... complexity. We propose a simple yet effective machine learning approach for a large set of known human SH2...”
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