Supplementary file 1_QSAR-guided discovery of novel KRAS inhibitors for lung cancer therapy.docx by Osasan Stephen Adebayo (22630082)

“…Following descriptor normalization and dimensionality reduction, five machine learning algorithm spartial least squares (PLS), random forest (RF), stepwise multiple linear regression (MLR), genetic algorithm optimized MLR (GA-MLR), and XGBoost were applied. …”

Table 2_QSAR-guided discovery of novel KRAS inhibitors for lung cancer therapy.xlsx by Osasan Stephen Adebayo (22630082)

“…Following descriptor normalization and dimensionality reduction, five machine learning algorithm spartial least squares (PLS), random forest (RF), stepwise multiple linear regression (MLR), genetic algorithm optimized MLR (GA-MLR), and XGBoost were applied. …”

Efficient Distributed Learning over Decentralized Networks with Convoluted Support Vector Machine by Canyi Chen (13532043)

“…First, we demonstrate that our generalized ADMM algorithm achieves linear convergence with a straightforward implementation. …”

Data Sheet 1_Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease.docx by Hsin-Yueh Liang (20887901)

“…We aimed to construct an artificial intelligence (AI)-based method to enhance ExECG performance to identify patients with significant coronary artery disease (CAD).…”

Data Sheet 1_Mathematical modeling reveals cell differentiation processes and progenitor kinetics necessary for proper nephrogenesis.docx by Matthew R. Hawkins (14129334)

“…</p>Methods<p>To investigate the potential drivers of nephron development from the population perspective, we incorporated traditional molecular tools for determining cellular characteristics as well as algorithmic based optimization methods. We synthesized multiple ODE based models to investigate hypotheses surrounding populations existing in early zebrafish nephron development.…”

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. …”

Data Sheet 1_A multimodal travel route recommendation system leveraging visual Transformers and self-attention mechanisms.pdf by Zhang Juan (11780753)

“…To effectively merge these two modalities, a self-attention mechanism fuses the visual features and sequential encodings, thoroughly accounting for their interdependencies. Based on this fused representation, a classification or regression model is trained using real travel datasets to recommend optimal travel routes.…”

Supplemental Figure S1. Height matching of ILD patients to control subjects by Alex Miller (19541772)

“…<p dir="ltr">Matches chosen using 1:1 nearest neighbor matching algorithm based on height of males (dark blue squares) and females (red circles) with ILD and control subjects. …”

Prediction intervals with controlled length in the heteroscedastic Gaussian regression by Christophe Denis (21538254)

“…The construction of the proposed algorithm is based on two samples, one labelled and another unlabelled. …”

Estimating Higher-Order Mixed Memberships via the l2,∞ Tensor Perturbation Bound by Joshua Agterberg (19727632)

“…We establish the identifiability of our model and propose a computationally efficient estimation procedure based on the higher-order orthogonal iteration algorithm (HOOI) for tensor SVD composed with a simplex corner-finding algorithm. …”

Data Sheet 2_Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province.xlsx by Li Luo (149019)

“…</p>Methods<p>Shotgun metagenomics sequencing was performed to analyze the gut microbiota of 381 unrelated Chinese Han individuals living in two cities (Wuhan and Shiyan) of Hubei Province. To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.…”

Data Sheet 1_Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province.docx by Li Luo (149019)

“…</p>Methods<p>Shotgun metagenomics sequencing was performed to analyze the gut microbiota of 381 unrelated Chinese Han individuals living in two cities (Wuhan and Shiyan) of Hubei Province. To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.…”

<b>A Single-cell Transcriptomic Sequencing Dataset of Early Female and Male Chicken (</b><b><i>Gallus gallus</i></b><b>) Embryos</b> by Zhi Cao (20682218)

“…The UMAP algorithm was optimized with a neighborhood size of 20 to achieve optimal cell clustering and clear visual representation of the cell populations.…”

A Four-Wavelength Photoplethysmography dataset for non-invasive hemoglobin assessment by Liang yongbo (4822017)

“…（<b>2023</b>）<a href="https://www.frontiersin.org/articles/10.3389/fphys.2023.1072273/full" target="_blank"><b>Link</b></a></p><p dir="ltr">[3] <b>Yongbo Liang</b>, Shimin Yin, Qunfeng Tang, Zhenyu Zheng, Mohamed Elgendi* and Zhencheng Chen*. Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals. …”

Analysis of kinematics and leveling performance of a novel cable-driven parallel automatic leveling robot for spacecraft hoisting by Zhuohong Dai (21215147)

“…A theoretical model of the cable adjustments is established and its adjustment scheme is analyzed and optimized. The relationship between the inclination angles and the counterweight adjustment displacement is established to better improve the levelling accuracy based on the force and torque balance principle. …”

Data Sheet 1_Association between admission Braden Skin Score and delirium in surgical intensive care patients: an analysis of the MIMIC-IV database.docx by Meiling Shang (21086624)

“…RCS models demonstrated a non-linear positive relationship between BSS and delirium. Based on RCS curves, the optimal threshold for BSS was established at 16, thereby categorizing participants into two groups: those with BSS < 16 and those with BSS ≥ 16. …”

Hyperspectral Camouflage Detection Dataset and Codes by Qiran Wang (22051883)

“…Hyperspectral data of camouflage fabrics and natural grass (389.06–1005.10 nm) were acquired and preprocessed using principal component analysis, standard normal variate transformation, Savitzky–Golay filtering, and derivative-based enhancement. The Sample set Partitioning based on joint X–Y distance (SPXY) algorithm was applied to improve representativeness of training subsets, and several classifiers were constructed, including SVM, RF, KNN, CNN, and ResNet. …”

CP-PPG: A Dual-Channel PPG Dataset for Studying the Impact of Contact Pressure on Blood Pressure Biosensing by Liang yongbo (4822017)

“…（<b>2023</b>）<a href="https://www.frontiersin.org/articles/10.3389/fphys.2023.1072273/full" target="_blank"><b>Link</b></a></p><p dir="ltr">[3] <b>Yongbo Liang</b>, Shimin Yin, Qunfeng Tang, Zhenyu Zheng, Mohamed Elgendi* and Zhencheng Chen*. Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals. …”

Data Sheet 1_Genome-wide expression in human whole blood for diagnosis of latent tuberculosis infection: a multicohort research.pdf by Fan Jiang (144211)

“…Cohorts were stratified into training (8 cohorts, n = 1,933) and validation sets (3 cohorts, n = 825) based on functional assignment.</p>Results<p>Through Upset analysis, LASSO (Least Absolute Shrinkage and Selection Operator), SVM-RFE (Support Vector Machine Recursive Feature Elimination), and MCL (Markov Cluster Algorithm) clustering of protein–protein interaction networks, we identified S100A12 and S100A8 as optimal biomarkers. …”

analysis_phd.xlsxMRP_PHD_DATA by MIHIR PANCHAL (20639651)

“…This paper presents a</p><p dir="ltr">novel approach for optimizing traffic signal control using deep Q-learning (DQL)</p><p dir="ltr">algorithms. …”