Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …”

Supplementary file 1_RadioMe: an automated home-based radio, music playlist, and diary reminder system: Report on recruitment, music compilation, and listening, and preliminary tes... by Alexander Street (16905678)

“…</p>Aims<p>RadioMe was a project designed for people living at home with dementia to build a system to help them maintain the highest quality of life there for as long as possible, with three functional components: 1. Streaming radio; 2. Providing pre-recorded spoken diary reminders; 3. interrupting the radio with pre-compiled playlists when a wrist-worn heart rate (HR) monitor detects stress. …”

Image_1_Bioinformatics Analysis Identifies Molecular Markers Regulating Development and Progression of Endometriosis and Potential Therapeutic Drugs.JPEG by Ying Peng (26452)

“…Furthermore, machine learning and LASSO algorithms identified three key genes, namely, apelin receptor (APLNR), C–C motif chemokine ligand 21 (CCL21), and Fc fragment of IgG receptor IIa (FCGR2A). …”

Image_1_Bioinformatics Analysis Identifies Molecular Markers Regulating Development and Progression of Endometriosis and Potential Therapeutic Drugs.JPEG by Ying Peng (26452)

“…Furthermore, machine learning and LASSO algorithms identified three key genes, namely, apelin receptor (APLNR), C–C motif chemokine ligand 21 (CCL21), and Fc fragment of IgG receptor IIa (FCGR2A). …”

Barro Colorado Island 50-ha plot aerial photogrammetry orthomosaics and digital surface models for 2018-2023: Globally and locally aligned time series. by Vicente Vasquez (13550731)

“…We first computed a grid of co-registration point using arosics.COREG_LOCAL function and used the highest reliability point position to globally align to the closest date orthomosaics. …”

Connectivity properties synthesized by the generative model. by Yifan Gu (1410265)

“…(<i><b>C</b></i>) The generated (dots) connection probabilities as a function of shared pre-synaptic common neighbors with different common neighbor coefficients <i>a</i>_Γ; the error bars show one SEM of 65 trials. …”

Least Bridges Graphs by Richard Frost (14064363)

“…This toolbox was originally created for analysis of values arising in genetic distance measures. The contained algorithms correct errors in commonly used nearest-neighbor and cluster software that are not designed with distances in mind (e.g. nearest-neighbor topology functions currently found in Python, SPSS, etc).…”

Credit analysis using data mining: application in the case of a credit union by Marcos de Moraes Sousa (5716367)

“…The goal of this study is to develop models to analyze the capacity of a credit union's members to settle their commitments, using a decision tree—C4.5 algorithm and an artificial neural network—multilayer perceptron algorithm. …”

Data_Sheet_1_Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development.DOCX by April R. Levin (4890703)

“…Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. …”

Table1_Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.pdf by Lijuan Liang (4277053)

“…We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. …”

Optimal Network Membership Estimation under Severe Degree Heterogeneity by Zheng Tracy Ke (8293395)

“…To obtain a rate-optimal method, we modify an existing spectral algorithm, Mixed-SCORE, by adding a pre-PCA normalization step. …”

Supplementary Material for: Coagulation risk predicting in anticoagulant-free CRRT by Liu L. (2945928)

“…Our machine learning models showed excellent predictive performance, with ensemble learning (EL) achieving an AUC of 0.863 (95% CI 0.860 - 0.868), outperforming individual algorithms. Random forest (RF) was the best single-algorithm model, with an AUC of 0.819(95% CI 0.814 - 0.823). …”

Data_Sheet_1_Multi-modal data combination strategy based on chest HRCT images and PFT parameters for intelligent dyspnea identification in COPD.ZIP by Yingjian Yang (14055882)

“…Second, the local features, including five selected pulmonary function test (PFT) parameters (SLF, 5), 28 selected lung radiomics (SLR, 28), and 22 selected 3D CNN features (S3C, 22), are respectively selected from the original 11 PFT parameters (OLF, 11), 1,316 OLR, and 13,824 O3C by the least absolute shrinkage and selection operator (Lasso) algorithm. …”

Table 1_Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.xlsx by XinPei Liu (16560699)

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”

Table 3_Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.xlsx by XinPei Liu (16560699)

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”

Table 2_Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.xlsx by XinPei Liu (16560699)

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”

Table 4_Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.xlsx by XinPei Liu (16560699)

“…LASSO regression identified 25 significant features for the models. Among the six algorithms tested, the radial basis function support vector machine (RBF-SVM) had the highest AUC at 0.771. …”

Table_2_Identification and Validation of Candidate Gene Module Along With Immune Cells Infiltration Patterns in Atherosclerosis Progression to Plaque Rupture via Transcriptome Anal... by Jing Xu (15337)

“…The gene set enrichment analysis (GSEA) was performed for interpreting the biological insights of gene expression data. The CIBERSORTx algorithm was applied to infer the relative proportions of infiltrating immune cells of the atherosclerotic samples. …”

Table_3_Identification and Validation of Candidate Gene Module Along With Immune Cells Infiltration Patterns in Atherosclerosis Progression to Plaque Rupture via Transcriptome Anal... by Jing Xu (15337)

“…The gene set enrichment analysis (GSEA) was performed for interpreting the biological insights of gene expression data. The CIBERSORTx algorithm was applied to infer the relative proportions of infiltrating immune cells of the atherosclerotic samples. …”

Table_1_Identification and Validation of Candidate Gene Module Along With Immune Cells Infiltration Patterns in Atherosclerosis Progression to Plaque Rupture via Transcriptome Anal... by Jing Xu (15337)

“…The gene set enrichment analysis (GSEA) was performed for interpreting the biological insights of gene expression data. The CIBERSORTx algorithm was applied to infer the relative proportions of infiltrating immune cells of the atherosclerotic samples. …”