Core data by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

From GIS to HBIM and Back: Multiscale Performance and Condition Assessment for Networks of Public Heritage Buildings and Construction Components by Teresa Fortunato (21076099)

“…GIS-based inventory approach of networked construction materials, components, and performances is established by unified performance descriptors and diagnostic tests. GIS-BIM data exchange routines by programming codes and algorithms are developed in Python. …”

Supplementary file 1_Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records.docx by Elizabeth Ford (381364)

“…Baseline and outcome coded diagnoses were supplemented with NLP-derived diagnosis data. …”

Additional file 1 of The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy by Szandra László (21420583)

“…There is provided further information about data collection and processing, machine learning algorithms, and other program codes, and more details about the findings…”

Table 1_Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection.docx by Jiayi Zheng (3441902)

“…The MG-SNN can learn to identify potential regions of moving targets through motion saliency estimation and subsequently integrates the information into the popular object detection algorithms to design the retinal-inspired spiking neural network module for drone motion extraction and object detection architecture, which integrates motion and spatial features before object detection to enhance detection accuracy. …”

Behavioral raw data recorded by HABITS autonomously by bowen yu (19822908)

“…Here, we present a home-cage assisted mouse behavioral innovation and testing system (HABITS), enables free-moving mice learn challenging cognitive behaviors in their home-cage without any human involvement. …”

Polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…<p dir="ltr">We have created a polyanion sodium cathode materials dataset that includes optimizations of structures to the lowest energy, ab initio molecular dynamics simulations trajectories sampled at 1000K, and structures generated from ML-driven molecular dynamics simulation at 1000K using active learning algorithms. The dataset consists of structures sampled from four sodium ion polyanionic cathode materials NaTMPO₄(olivine) ,NaTMPO₄(maricite), Na₂TMSiO₄ and Na_2.56TM_1.72(SO₄)₃ , along with various structures incorporating doping of transition metal ions (TM). …”

Table 1_Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma.docx by Xiang Xiong (1810234)

“…</p>Methods<p>The TCGA database was utilized to obtain RNA-seq-based transcriptome profiling data, clinical information, and mutation data. We conducted multivariate Cox regression analysis to identify alkaliptosis-related lncRNAs. …”

Video 1_TDE-3: an improved prior for optical flow computation in spiking neural networks.mp4 by Matthew Yedutenko (5142461)

“…We conducted an in-depth quantitative investigation of optical flow coding with TDE and compared TDE-2 vs. TDE-3 in terms of energy efficiency and coding precision. …”

Info-graphics summarising how to navigate the field of AI in the form of a tube (metro) map. by Aidan Crilly (21743791)

“…The rules in this paper are ordered according to the flow of scientific explorations: Framing the scientific problem and finding AI algorithms (Zone 2), coding (Zone 3), and testing and interpreting results (Zone 4). …”

<b>Supplementary Materials for:</b> <b>Pan-Cancer Analysis Reveals LncRNA CDKN2B-AS1 as an Immune-Related Biomarker Validated in LIHC and ACC</b> by Dandan Lin (18192946)

“…This study comprehensively investigates the role of the long non-coding RNA CDKN2B-AS1 in cancer prognosis and tumor microenvironment across multiple cancer types using bioinformatic analyses.…”

Presentation1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.pdf by Qingliu He (12528332)

“…</p>Methods<p>Circular_seq was used in conjunction with the TCGA-PRAD transcriptome dataset to sequence, annotate, and filter for eccDNA-amplified differentially expressed coding genes (eDEGs) in PRAD and para-cancerous normal prostate tissues. …”

Image 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.tif by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 9_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 6_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 3_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 7_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 10_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 2_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 5_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”