PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…<p dir="ltr">The first algorithm for segmentation and localization (see PathOlOgics_script_1; segment & localize using a pen) relied on manually tracing the borders of each cell using a digital pen tool on a big touchscreen display showing source images/patches. …”

The result for the risk assessment on three datasets using different optimal methods. by Jiaqing Huang (5018492)

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Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Comparison of optimization performance of six ABC algorithms. by Shuhui Yu (1535500)

Functional profiling of GS height <i>preserved</i> modules with cumulative evidence for genomic risk effect on co-expression. by Eugenia Radulescu (319733)

Functional profiling of GS-SCZ <i>preserved</i> modules with cumulative evidence for genomic risk effect on co-expression. by Eugenia Radulescu (319733)

The result for the risk assessment on A, B, C bank using different features. by Jiaqing Huang (5018492)

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Algorithmic process of partial convolution. by Cuiying Yu (18437285)

Plot of coverage attenuation function. by Junjie He (700642)

Subjects: “…coverage attenuation function…”

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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MTLBO-BP prediction model process. by Huazan Liu (9137461)

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Prediction percentage error. by Huazan Liu (9137461)

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Test data and parameters. by Huazan Liu (9137461)

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Average training time. by Huazan Liu (9137461)

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BP neural network structure diagram. by Huazan Liu (9137461)

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S1 Data - by Huazan Liu (9137461)

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Basic information of each subsystem. by Huazan Liu (9137461)

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Feature selection algorithm. by Mahmoud Zeydabadinezhad (12289570)

“…Our analysis pipeline included pre-processing steps, feature extraction from both time and frequency domains, a voting algorithm for selecting features, and model training and validation. …”

Risk and density functions for standard relapse from remission condition to disease <i>b</i> condition (similar shapes for standard relapse to disease <i>a</i>). by Benoîte de Saporta (20454662)

Python implementation from Symplectic decomposition from submatrix determinants by Jason L. Pereira (11598632)

“…Python implementation of the algorithm and demonstration of how to use the functions.…”