Python code for: Using convolutional neural network to predict remission of diabetes after gastric bypass surgery – a machine learning study from the Scandinavian Obesity Surgery Register by Yang Cao (9509135)

“…<p>The file includes the Python code and annotations of training, validation, and test for the CNN predictive model used in the paper “Using convolutional neural network to predict remission of diabetes after gastric bypass surgery – a machine learning study from the Scandinavian Obesity Surgery Register”.…”

Hyperparameters of the ProSmith gradient boosting models. by Alexander Kroll (9304225)

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Experimental results for solar melting of zinc metal using multi-facet parabolic dish and a cavity receiver by Pieter Bezuidenhout (18333273)

“…</p> <p>Experiments were conducted, each with a unique set of environmental conditions:</p> <ol> <li>Experiment 1 – 26^th of July 2022 = “Exp 1_26072022”</li> <li>Experiment 2 – 04t of August 2022= “Exp 2_04082022”</li> <li>Experiment 3 – 16^th of August 2022= “Exp 3_16082022”</li> <li>Experiment 4 – 21^st of August 2022= “Exp 4_21082022”</li> <li>Experiment 5 – 5^th of September 2022= “Exp 5_05092022”</li> </ol> <p>Also included in the dataset are the original weather data collected on the respective experimental test work days as well as the weather data in the processed form after correcting the weather data to serve as input for the numerical model developed in the Python coding language.</p> <p>Raw weather data:</p> <ol> <li>Exp 1_Weather data_Original_26072022</li> <li>Exp 2_Weather data_Original_04082022</li> <li>Exp 3_Weather data_Original_16082022</li> <li>Exp 4_Weather data_Original_21082022</li> <li>Exp 5_Weather data_Original_05092022</li> </ol> <p>Processed weather data:</p> <ol> <li>Exp 1_Weather data_Post-process_26072022</li> <li>Exp 2_Weather data_Post-process_04082022</li> <li>Exp 3_Weather data_Post-process_16082022</li> <li>Exp 4_Weather data_Post-process_21082022</li> <li>Exp 5_Weather data_Post-process_05092022</li> </ol> <p>In addition to all the weather data and the experimental results collected on the five experimental runs, the dataset also contains the Python code used to predict the zinc temperature in the cavity receiver. …”

The optimal ProSmith models combine predictions based on the multimodal Transformer Network with predictions based on separate numerical representations of proteins and small molec... by Alexander Kroll (9304225)

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Scheme of hippocampal detection and prediction of MTLE with the hippocampus as the epileptogenic area. by Kyoya Sakashita (14670611)

Predictive performance for earthworm species prediction across different classification models and handcrafted features on external validation dataset (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

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Predictive performance for earthworm species prediction across different classification models and deep feature maps on external validation dataset (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

Predictive performance for earthworm species prediction across different classification models and handcrafted features using 10-fold CV (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

Fig 4 - by Xiujie Ge (6831833)

<b>Python codes for machine learning algorithms for subclinical mastitis prediction</b> by Hamza Yalçin (21182759)

Predictive performance for earthworm species prediction across different classification models and deep feature maps using 10-fold CV (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

Deep learning models to identify penguins' prey capture rates by Stefan Schoombie (6844115)

“…This as done in the Python programming language.</p><p dir="ltr">Two models were trained (CNN and V-Net architectures) and predictions were made on individual birds that have not been exposed to the model training.…”

Python Script for the QSAR Model Building. by Md. Al-Amin (6270104)

Replacing the final prediction layer of end-to-end trained Transformer Networks with gradient boosting models improves performance. by Alexander Kroll (9304225)

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A Preliminary Analysis On the Diffusion of Python-Specific Code Smells in AI-Enabled Systems by Giusy Annunziata (14860255)

Five Operator Lattice Simulation by James McDaniel (22522571)

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ProSmith outperforms the ESP model in the prediction of enzyme-substrate pairs especially for molecules with limited representation in the test data. by Alexander Kroll (9304225)

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Performance metrics for all three trained gradient boosting models with different input vectors and for their combined weighted mean prediction. by Alexander Kroll (9304225)

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Motif Code Theory Figshare Documentation by William Terry (22279591)

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