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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Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. 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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Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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PyNoetic’s channel selection module, which supports various channel selection criteria including CSP, correlation, Mutual Information, and Chi-squared. by Gursimran Singh (575288)

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Tunable parameters in stimuli generation module. ^<i>a</i>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

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Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Performance of various deep learning models from PyNoetic’s classification module on the Motor Imagery decoding task. by Gursimran Singh (575288)

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Illustration of recording paradigm with PyNoetic’s Stimuli generation and recording module. by Gursimran Singh (575288)

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Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Supplementary file 1_Identifying gastric intestinal metaplasia risk based on clinical indicators: a machine learning predictive model based on the SHAP methodology.xls by Yufen Wang (827997)

“…Initially, the VarSelRF algorithm identified independent variables linked to GIM development. …”

Augmentation effects on least accurate performance. by John Kruper (18809386)

Success convergence rates of the four methods. by Huanyu Yang (6683780)

“…The sub-block selection algorithm sorts and filters sub-blocks based on the average pixel difference, reconstructing the input data to ensure accurate separation of melanin and hemoglobin. …”

Assign initial cluster centers. by Huanyu Yang (6683780)

“…The sub-block selection algorithm sorts and filters sub-blocks based on the average pixel difference, reconstructing the input data to ensure accurate separation of melanin and hemoglobin. …”

Augmentation effects on best performance. by John Kruper (18809386)

Supplementary file 1_Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records.docx by Elizabeth Ford (381364)

“…A transdiagnostic risk calculator, predicting psychosis using electronic health record (EHR) data, was developed in London, UK to identify patients at risk, using structured data and 14 natural language processing (NLP)-derived symptom and substance use concepts. …”

Schematic representation of Ig-domains dimerization patterns and contact network A) VH:VL schematic parallel interface and conserved interactions B) CH1:CL schematic antiparallel i... by Caesar Tawfeeq (21087272)