DeepB3Pred_source_code by Muhammad Arif (17012472)

Flow diagram detailing the number of radiographs by data source and abnormality status from before exclusion for age (All Ages), after exclusion for age under 15 years, and after e... by Scott H. Lee (7430396)

OVEP code by Yuanfang Guan (22258765)

“…</p><p><br></p><p><br></p><p>---</p><p><br></p><p dir="ltr">## Directory structure (top-level)</p><p><br></p><p dir="ltr">- `rate_code/` </p><p>---</p><p><br></p><p dir="ltr">## Key scripts </p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation/calculate_predicted_snp_by_category_maskfunctional.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category maskfunctional.py</p><p dir="ltr">- `rate_code/revision/JARVIS/modules/jarvis/deep_learn_raw_seq/for_prediction_train_nn_model.py` </p><p dir="ltr"> Arg 'input_features' may take 1 of 3 possible values: - stuctured: using only structured features as input - sequence: using only sequence features as input - both: using both structured and sequence features as inputs</p><p dir="ltr">- `rate_code/revision/JARVIS/modules/jarvis/variant_classification/plot_gb_feature_importance.py` </p><p dir="ltr"> Script related to: plot gb feature importance.py</p><p dir="ltr">- `rate_code/external_test/calculate_AUC_dataset1_masksnp.py` </p><p dir="ltr"> Script related to: calculate AUC dataset1 masksnp.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation_calibration/calculate_predicted_snp_by_category.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation_calibration_masklabel/calculate_predicted_snp_by_category_new.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category new.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation_calibration_masklabel/calculate_predicted_snp_by_category.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation_calibration_maskfunctional_maskrepeat/calculate_predicted_snp_by_category.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation/calculate_predicted_snp_by_category.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation/calculate_predicted_snp_by_category_nolabel.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category nolabel.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/exon_analysis_masklabel/calculate_predicted_snp_by_exon_mask.py` </p><p dir="ltr"> Script related to: calculate predicted snp by exon mask.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/category_annotation_calibration_maskfunctional/calculate_predicted_snp_by_category.py` </p><p dir="ltr"> Script related to: calculate predicted snp by category.py</p><p dir="ltr">- `rate_code/post_analysis_maskmissing/exon_analysis/calculate_predicted_snp_by_exon_mask.py` </p><p dir="ltr"> Script related to: calculate predicted snp by exon mask.py</p><p dir="ltr">- `rate_code/code_halftrainmaskmissing_masklabel/base_excludeN_5fold_nonindelonlyintest_masklabel/predict_nucleotide_plot.py` </p><p dir="ltr"> Script related to: predict nucleotide plot.py</p><p dir="ltr">- `rate_code/code_halftrainmaskmissing_masklabel/base_excludeN_5fold_nonindelonlyintest_masklabel/predict_train.py` </p><p dir="ltr"> Script related to: predict train.py</p><p dir="ltr">- `rate_code/code_halftrainmaskmissing_masklabel/base_excludeN_5fold_indelonlyintest_masklabel/predict_nucleotide_plot.py` </p><p dir="ltr"> Script related to: predict nucleotide plot.py</p><p dir="ltr">- `rate_code/code_halftrainmaskmissing_masklabel/base_excludeN_5fold_indelonlyintest_masklabel/predict_train.py` </p><p dir="ltr"> Script related to: predict train.py</p><p dir="ltr">- `rate_code/code_halftrainmaskmissing_masklabel/plot/plot_indel_snp_auc.py` </p><p dir="ltr"> !…”

Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

A model of neural population dynamics for flexible sensorimotor control by Hari Kalidindi (17123467)

Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research by Temitope Omogbene (18615415)

“…</li><li><b>Dataset 1D (highlighted_full_data_with_predictions.xlsx):</b> The complete harmonised dataset automatically classified using the trained XGBoost model.…”

Computing speed and memory usage. by David Berling (22170661)

“…Evaluation of the original model for different spatial volumes was not possible due to hard coding of these parameters in the published application. …”

6. Motif Code Theory by William Terry (22279591)

“…<p dir="ltr">The Motif Code Theory (MCT) simulation code, mct_unified_code.py, is a Python 3.9 script that models the universe as a time-dependent directed multigraph G(t) = (V(t), E(t)) with N=10^7 vertices (representing quantum fields/particles) and edges (interactions). …”

Modeling flowchart. by Jingru Dong (14076094)

“…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …”

Table 1_Machine learning models for mortality prediction in patients with spontaneous subarachnoid hemorrhage following ICU treatment.docx by Wenwen Hu (403536)

“…</p>Conclusions<p>In our study, the LR model exhibited superior discrimination in predicting risk of mortality among patients with spontaneous SAH compared to other models. …”

Image 1_Machine learning models for mortality prediction in patients with spontaneous subarachnoid hemorrhage following ICU treatment.jpeg by Wenwen Hu (403536)

“…</p>Conclusions<p>In our study, the LR model exhibited superior discrimination in predicting risk of mortality among patients with spontaneous SAH compared to other models. …”

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

“…</p><h3><b>Model training</b></h3><h4><code>python train_GTN.py</code></h4><p dir="ltr">This step trains the GTN model. …”

Evaluation Metrics for LSTM Model and GRU Model. by Majed Alzara (20700224)

“…This study creates a predictive model just for Egypt’s construction industry that aims to predict a localized CCI to improve financial planning and lower risk. …”

Pythonproject-HCC by Roy Zhao (22503761)

BGC-Prophet by Haohong Zhang (17911673)

“…/output/ --name split --threads 10</code></pre><p dir="ltr"><b>4. Gene Prediction</b></p><p dir="ltr">Detect BGC genes using a trained model:</p><pre><code>bgc_prophet predict --datasetPath .…”

Probabilities of normal and various cyber attack types over time sequence. by Mohanad Faeq Ali (21354273)

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Graphical abstract of HCAP. by Mohanad Faeq Ali (21354273)

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Recall analysis. by Mohanad Faeq Ali (21354273)

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FPR and FNR analysis based on varying cyber attack types. by Mohanad Faeq Ali (21354273)

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Analysis of IoMT data sources. by Mohanad Faeq Ali (21354273)

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