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sample detection » sample selection (Expand Search), damage detection (Expand Search), sample collection (Expand Search)
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Supplementary Material for: Detecting atrial fibrillation by artificial intelligence enabled neuroimaging examination.
Published 2025“…Background Diagnosis of occult atrial fibrillation (AF) is difficult as it is often asymptomatic, leading to under detection. Current diagnostic tests have variable limitations in feasibility and accuracy. …”
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Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf
Published 2024“…We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset.…”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…Here, we propose a solution to address the limitation of identifiable motor activities by using combined MIs (i.e., MIs involving 2 or more body parts at the same time). And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
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Equivalent Mutants Analysed via Deductive Verification
Published 2025“…</p><p dir="ltr">Most of the samples selected above lacked loops. We therefore added three search algorithms: BinarySearch, FindLast and FindMin.…”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay
Published 2025“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”
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Fig 3 -
Published 2024“…Role of ICT in this algorithm shown diagrammatically.</b> C. <b>Representative example of ICT detecting very early seroconversion using sera originally stored for another purpose tested retrospectively, showing contrast with false positives.…”
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Data_Sheet_1_Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases.P...
Published 2021“…As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. …”
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Raw LC-MS/MS and RNA-Seq Mitochondria data
Published 2025“…The data were filtered as follows: (a) binary expression of a protein (i.e., protein exclusively identified in either scLRP1+/+ or scLRP1-/-) was only considered relevant if all scLRP1+/+ samples or all scLRP1-/- samples expressed the protein. …”