Settings for ABC-SMC code. by Román Zapién-Campos (9592478)

Comparison of previous predictive models. by Saeid Rasouli (20370998)

“…<div><p>Background</p><p>Optic neuritis (ON) can be an initial clinical presentation of multiple sclerosis This study aims to provide a practical predictive model for identifying at-risk ON patients in developing MS.…”

The ROC, calibration curve and DCA of the combined prediction model based on tumor diameter combined with the optimal radiomics features. by Jiangfa Li (18345033)

Subjects:

DeepB3Pred - code by Saleh Musleh (22263718)

ZILLNB_Model by Qinhuan Luo (21288548)

“…<p dir="ltr">Acquire latent variables using deep-learning based model implemented in python</p>…”

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

“…To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …”

Table 1_Entropy-adaptive differential privacy federated learning for student performance prediction and privacy protection: a case study in Python programming.docx by Shanwei Chen (12031760)

“…This study proposes an Entropy-Adaptive Differential Privacy Federated Learning method (EADP-FedAvg) to enhance the accuracy of student performance prediction while ensuring data privacy. Based on online test records from Python programming courses for Electronic Engineering students (grade 2021–2023) at the School of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, China, the study uses a Multilayer Perceptron (MLP) model and 10 distributed clients for training. …”

Optimal radiomics feature of MRI. by Jiangfa Li (18345033)

Subjects:

Optimal radiomics feature of CT. by Jiangfa Li (18345033)

Subjects:

Extracted CT and MRI images and outlined ROI. by Jiangfa Li (18345033)

Subjects:

Statistically relevant information. by Jiangfa Li (18345033)

Subjects:

Cross-validation of Lasso regression of enhanced MRI images. by Jiangfa Li (18345033)

Subjects:

Univariate and multivariate results of MVI-positive and MVI-negative in training group. by Jiangfa Li (18345033)

Subjects:

The cross-validation diagram of Lasso regression of enhanced CT combined with MRI images. by Jiangfa Li (18345033)

Subjects:

Cross-validation of Lasso regression of enhanced CT images. by Jiangfa Li (18345033)

Subjects:

Comparison of general clinical data between training group and verification group. by Jiangfa Li (18345033)

Subjects:

Optimal radiomics features of CT combined with MRI. by Jiangfa Li (18345033)

Subjects:

Partial Rank Correlation Coefficient (PRCC) sensitivity analysis results, obtained using LHS with 1000 samples and run in Python version 3.11.0. by Tinashe Victor Mupedza (22022124)

DeepB3Pred_source_code by Muhammad Arif (17012472)

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Subjects: