Effect of segmentation error on Leiden clustering. by Matthias Bruhns (22250913)

Data Sheet 2_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.pdf by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Data Sheet 1_Integration of single-cell sequencing and machine learning identifies key macrophage-associated genetic signatures in lumbar disc degeneration.pdf by Hongxing Zhang (209372)

“…A panel of 101 machine learning algorithms was employed to screen diagnostic genes, with ROC curves used for validation. …”

Data Sheet 1_Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology.docx by Xihui Yu (19945377)

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…<p dir="ltr">This dataset contains the data used in the article <a href="https://academic.oup.com/aob/advance-article/doi/10.1093/aob/mcaf043/8074229" rel="noreferrer" target="_blank">"Machine Learning and digital Imaging for Spatiotemporal Monitoring of Stress Dynamics in the clonal plant Carpobrotus edulis: Uncovering a Functional Mosaic</a>", which includes the complete set of collected leaf images, image features (predictors) and response variables used to train machine learning regression algorithms.…”

Data Sheet 1_Integrative single-cell and machine learning analysis predicts lactylation-driven therapy resistance in prostate cancer: a molecular docking and experiments-validated... by Zhiyu Liu (739871)

“…</p>Results<p>In this study, a model composed of 29 biomarkers was developed by integrating single-cell data and machine learning algorithms. The model predictive efficacy was validated through Kaplan-Meier (KM) analysis, univariate Cox (HR=3.59, 95%CI: 2.78-4.63) and multivariate Cox (HR=2.81, 95%CI: 1.96-4.03) regression. …”

Data Sheet 1_Better performance of cerebral blood volume images synthesized from arterial spin labeling and standard MRI in separating glioblastoma recurrence from treatment respon... by Danyang Wu (6751385)

Table 1_Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth... by Jiahe Liu (9096353)

“…Our study aimed to examine the risk factors associated with IA among Chinese children and adolescents and leverage explainable machine learning (ML) algorithms to predict IA status at the time of assessment, based on Young’s Internet Addiction Test.…”

Data Sheet 2_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

Data Sheet 1_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

Data Sheet 3_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

The architecture of the SE-multi-input CNN model. by Bin Zheng (45359)

“…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …”

Confusion matrix for the Multi-input CNN model. by Bin Zheng (45359)

“…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …”

Confusion matrices for single-input CNN models. by Bin Zheng (45359)

“…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …”

Confusion matrix for the Multi-input CNN model. by Bin Zheng (45359)

“…The fusion strategy combines feature maps via bicubic interpolation and element-wise summation to maintain spatial integrity. …”

Pipeline for extraction of parameters for ML and DL. by John Kruper (18809386)

“…<p>(A) Diffusion MRI (dMRI) data from the HBN-POD2 sample is used as input to the algorithm. …”

Steps to the final sample. by Vittorio Nicoletta (21367878)

“…<div><p>One major obstacle to advancing research and treatment for major psychiatric disorders is their substantial within-diagnosis heterogeneity in patient lifetime trajectories. Adapted research methods such as cluster analysis to define subgroups of patients are currently used. …”

Structure of Dense Block. by Nadim Rana (11424583)

“…Significant features are extracted from the images using an Enhanced Auto-Encoder (EnAE) model, which combines a stacked auto-encoder architecture with an attention module to enhance feature representation and classification accuracy. …”

Design of DenseNet. by Nadim Rana (11424583)

“…Significant features are extracted from the images using an Enhanced Auto-Encoder (EnAE) model, which combines a stacked auto-encoder architecture with an attention module to enhance feature representation and classification accuracy. …”

Assessment Using Dataset 2. by Nadim Rana (11424583)

“…Significant features are extracted from the images using an Enhanced Auto-Encoder (EnAE) model, which combines a stacked auto-encoder architecture with an attention module to enhance feature representation and classification accuracy. …”