Impact of class imbalance. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Construction of non-invasive diagnostic model and nomogram of AR. by Xihao Shen (20347942)

Decoding motor patterns as a function of word length. by Viet Chau Linh Nguyen (21601707)

“…(C) Average number of fixations in good (blue dots) and poor decoders (red dots) as a function of word length (expressed in number of characters) in both training sessions. …”

Data Sheet 1_Advances in HD-EMG interfaces and spatial algorithms for upper limb prosthetic control.pdf by Debora Quadrelli (22179796)

“…This mini-review explores advancements in HD-EMG acquisition systems, including both interface designs and recording technologies, as well as ML algorithms leveraging spatial information. …”

A hypothetical example illustrating the differences between the two assessment modes in G4SNVHunter. by Rongxin Zhang (1618159)

Overview of archaic SNPs (aSNPs) potentially affecting G4 formation, identified by G4SNVHunter. by Rongxin Zhang (1618159)

Reactive Molecular Simulation and Microscopic Origins in the Reaction Kinetics of Binary Polymerization by Xinwei Chen (255125)

“…A microscopic expression of the hybrid function is derived based on the general collision reaction model and reactive algorithm in molecular dynamics (MD) simulation, in which both the reaction energy barrier and intermolecular interaction play pivotal roles. …”

Overnight technician routing and scheduling problem with time windows and balanced workloads: a bi-objective zebra optimization algorithm by Abolfazl Gharaei (21803416)

“…</p> <p><b>Highlights</b></p><p>An ML-based bi-objective zebra optimisation algorithm to treat large-scale TRSPs</p><p>Centroid-based clustering on the population of zebras to avoid bias towards a specific search space</p><p>Making a trade-off between exploration and exploitation of the feasible region in the developed algorithm</p><p>A new MINLP model of a weighted bi-objective TRSP with limited capacity depots</p><p>Workload function, penalty function for lateness, subcontracts, time windows for tasks and breaks</p><p>Experiments using real data to show the performance of the model and solution method</p><p></p> <p>An ML-based bi-objective zebra optimisation algorithm to treat large-scale TRSPs</p> <p>Centroid-based clustering on the population of zebras to avoid bias towards a specific search space</p> <p>Making a trade-off between exploration and exploitation of the feasible region in the developed algorithm</p> <p>A new MINLP model of a weighted bi-objective TRSP with limited capacity depots</p> <p>Workload function, penalty function for lateness, subcontracts, time windows for tasks and breaks</p> <p>Experiments using real data to show the performance of the model and solution method</p>…”

Optimal Subsampling for Functional Quasi-Mode Regression with Big Data by Tao Wang (12008)

“…<p>We propose investigating optimal subsampling for functional regression with massive datasets based on the mode value, which is referred to as functional quasi-mode regression, to reduce data volume and alleviate computational burden. …”

Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Deep Neural Network for Functional Graphical Models Structure Learning by Shuoyang Wang (22127443)

“…We discover a novel critical sampling frequency that governs the convergence rates of the deep neural network estimator for both densely and sparsely observed functional data. …”

Effect of Mitophagy Score on Immunotherapy for Different Datasets. by Jie Chu (293795)

Raw data of Cell experiments. by Jie Chu (293795)

“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”

GSEA analysis. by Jie Chu (293795)

“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”

Baseline data table. by Jie Chu (293795)

“…The characteristics of the immune microenvironment were assessed using the CIBERSORT R package. Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”