Test data on mining capacity. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Comparison of standard GEP and DGEP. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Test data on population diversity. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization by Stephanos Karafiludis (12902591)

“…This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials.…”

Flowchart of the DGEP process. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Comparison of the ability to escape local optima. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization by Stephanos Karafiludis (12902591)

“…This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials.…”

High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization by Stephanos Karafiludis (12902591)

“…This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials.…”

Statistical analysis of DGEP vs. standard GEP. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization by Stephanos Karafiludis (12902591)

“…This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials.…”

Schematic representation of selected data from the Allen Institute dataset. by Saeed Mohammadzadeh (13492285)

Application of explainable clustering on cell features for unsupervised organization scoring. by Saeed Mohammadzadeh (13492285)

Interactive visualization of ocean unsteady flow data based on dynamic adaptive pathline by Fenglin Tian (6002957)

“…This study presents an interactive visualization algorithm designed for the spatio-temporal correlated ocean unsteady flow field utilizing dynamic adaptive pathlines. …”

ProSAAS is expressed in multiple cell types in a mixed species meta-analysis. by Nicholas Schaffer (21376843)

Table 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.xlsx by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”

Image 3_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”

Image 1_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”

Image 2_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”

Image 7_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”

Image 6_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif by Hanzhang Lyu (22163404)

“…</p>Results<p>Plexin-A3 (PLXNA3) emerged as a top risk gene within the ensemble model, which achieved strong predictive performance, surpassing conventional clinical indicators. …”