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

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The training process for PV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for AV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for TV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for MV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

FFD control body frame diagram. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

Changes in the relative abundances of signaling functions across initial GA-LR pairs. by Erick Armingol (5125595)

Benchmark functions. by Qinghe Guo (21519322)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

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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Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Supplementary Material for: A radiomics-based analysis of functional dopaminergic scintigraphic imaging for the diagnosis of dementia with Lewy bodies by figshare admin karger (2628495)

“…Introduction Radiomics features, a technique based on quantitative image analysis, can be used to capture tissue and lesion characteristics, such as heterogeneity and shape. Using functional dopaminergic scintigraphy, we aim to study the value of radiomics features in predicting the diagnosis of dementia with Lewy bodies (DLB). …”

Kinematics timeries and features of cluster 1 before and one year after surgery. by Xavier Gasparutto (8374578)

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Kinematics timeries and features of cluster 3 before and one year after surgery. by Xavier Gasparutto (8374578)

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Spatiotemporal parameters for patients clusters (before and one year after surgery) and control group. by Xavier Gasparutto (8374578)

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Characteristics and patients reported outcomes for patient clusters before and one year after surgery compared to the control group. by Xavier Gasparutto (8374578)

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Implant characteristics of the whole cohort, datasets and clusters. by Xavier Gasparutto (8374578)

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Kinematics timeseries and features for patients clusters, with between clusters comparison. by Xavier Gasparutto (8374578)

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Kinematic features for all patients before (PRE) and one year after surgery (P1Y) as well as all control group values. by Xavier Gasparutto (8374578)

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Kinematics timeries and features of cluster 2 before and one year after surgery. by Xavier Gasparutto (8374578)

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