Table_2_From Patient-Controlled Analgesia to Artificial Intelligence-Assisted Patient-Controlled Analgesia: Practices and Perspectives.docx by Rui Wang (52434)

“…Integrating the big data collected by state-of-the-art monitoring sensors, the Internet of Things and AI algorithms, an AI-assisted PCA (Ai-PCA) may be a promising future direction for postoperative pain management.…”

Table_1_From Patient-Controlled Analgesia to Artificial Intelligence-Assisted Patient-Controlled Analgesia: Practices and Perspectives.docx by Rui Wang (52434)

“…Integrating the big data collected by state-of-the-art monitoring sensors, the Internet of Things and AI algorithms, an AI-assisted PCA (Ai-PCA) may be a promising future direction for postoperative pain management.…”

Image_1_From Patient-Controlled Analgesia to Artificial Intelligence-Assisted Patient-Controlled Analgesia: Practices and Perspectives.pdf by Rui Wang (52434)

“…Integrating the big data collected by state-of-the-art monitoring sensors, the Internet of Things and AI algorithms, an AI-assisted PCA (Ai-PCA) may be a promising future direction for postoperative pain management.…”

Table_3_From Patient-Controlled Analgesia to Artificial Intelligence-Assisted Patient-Controlled Analgesia: Practices and Perspectives.docx by Rui Wang (52434)

“…Integrating the big data collected by state-of-the-art monitoring sensors, the Internet of Things and AI algorithms, an AI-assisted PCA (Ai-PCA) may be a promising future direction for postoperative pain management.…”

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)

Dataset for 'An Automated Workflow of Deep Learning Ensemble Model with Principal Component Analysis for Enhanced Material Characterisation in Energy Dispersive Spectroscopy' by Fanzhi Su (21005174)

Average accuracy (across all 12 subject) as a function of the number of eigenvectors obtained with different dimensionality reduction techniques for the best classifier—k-NN (see a... by Elnaz Lashgari (11278808)

Identification of Microbial Strains via 2D Cross-Correlation of LC-MS Data by Tucker James Collins (18552609)

“…Prior research in this area has employed methods such as Principal Component Analysis (PCA), the k-Nearest Neighbors’ (kNN) algorithm, and Pearson correlation. …”

S1 File - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

S1 Dataset - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

Protection of data-inferred tasks reduces the influence of extraction methods on model content. by Anne Richelle (6589178)

Code For Use in a Bookកូដសម្រាប់ប្រើប្រាស់ក្នុងសៀវភៅ by Sarun Horn (20899271)

Pseudo live-stream of EEG data is processed through the flow chart: after channel selection, each epoch undergoes Kaiser windowing (length = 250), followed by re-referencing to the... by Gursimran Singh (575288)

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PyNoetic’s online mode in action. Data is streamed from an Emotiv EPOC headset. by Gursimran Singh (575288)

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Illustration of PyNoetic’s 2D and 3D simulation module with visual feedback. by Gursimran Singh (575288)

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PyNoetic’s unique pick-place configurable flowchart that offers a no-code option for non-programmers. by Gursimran Singh (575288)

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PyNoetic’s feature extraction module that supports time domain features, frequency domain features, time-frequency domain features, spatial features as well as Brain Connectivity m... by Gursimran Singh (575288)

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Pseudo live-stream of EEG data is generated, and a simple pick-and-place flowchart is designed for channel selection and filtering. by Gursimran Singh (575288)

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List of Abbreviations by Gursimran Singh (575288)

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PyNoetic’s stimuli generation and recording module, which supports both ERP and SSVEP. by Gursimran Singh (575288)

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