Table 5_Exploring the diagnostic potential of IL1R1 in depression and its association with lipid metabolism.xlsx حسب Yao Gao (1420339)

"…Subsequently, support vector machine (SVM) and random forest algorithms were employed to determine the optimal division of feature variables. …"

Table 1_Research trends and hotspots evolution of artificial intelligence for cholangiocarcinoma over the past 10 years: a bibliometric analysis.docx حسب Ke-xie Wang (20718248)

"…Early research primarily focused on traditional treatment methods and care strategies for CCA, but since 2019, there has been a significant shift towards the development and optimization of AI algorithms and their application in early cancer diagnosis and treatment decision-making. …"

Modelling of intrinsic membrane permeability of drug molecules by explainable ML-based q-RASPR approach towards better pharmacokinetics and toxicokinetics properties حسب I. Dasgupta (1276581)

"…In the present work, our focus is on the construction of a machine learning (ML)-based quantitative read-across structure–property relationship (q-RASPR) model of intrinsic permeability of drug molecules by utilizing both linear and non-linear algorithms. The Support Vector Regression (SVR) q-RASPR model was found to be the best model having superior predictive ability (<i>Q</i>²_F1 = 0.788, <i>Q</i>²_F2 = 0.785, <i>MAE</i>_test = 0.637). …"

Supplementary Material for: Extracellular vesicle-based urinary proteomic signatures predict remission and relapse in primary membranous nephropathy حسب figshare admin karger (2628495)

"…A prognostic model was developed by screening 101 machine learning algorithms, with the final risk score derived from a random survival forest and stepwise Cox regression, internally validated via bootstrap resampling. …"

Unveiling the role of oxidative stress in ANCA-associated glomerulonephritis through integrated machine learning and bioinformatics analyses حسب Liyuan Xie (1846459)

"…Then, by integrating weighted gene co-expression network analysis, and machine learning algorithms, we identified four upregulated hub OSRGs (all <i>p</i> < 0.01) with strong diagnostic potential (all AUC > 0.9)-CD44, ITGB2, MICB, and RAC2 – in the AAGN glomerular training dataset GSE104948 and validation dataset GSE108109, along with two hub OSRGs (all <i>p</i> < 0.05) with better diagnostic potential (all AUC > 0.7) – upregulated gene VCAM1 and downregulated gene VEGFA-in the AAGN tubulointerstitial training dataset GSE104954 and validation dataset GSE108112. …"

Estilometría TIP: enhanced text analysis tool with customisable metrics for Spanish texts حسب Francisco J. Carreras-Riudavets (20562834)

"…Lexicon TIP draws on a comprehensive database of more than 320,000 lemmas and 8 million inflected forms, accounting for variations in number, gender, superlatives, diminutives, augmentatives, derogatory terms, and verb conjugations. Two key algorithms enhance this functionality: prefix detection, which accurately identifies prefixed words (e.g. …"

Table 1_Genetic analysis of non-syndromic peg lateralis using whole-exome sequencing.xlsx حسب Junglim Choi (22045838)

"…In-silico mutation impact analysis was performed using Polymorphism Phenotyping v2, sorting intolerant from the tolerant, and integrated score of co-evolution and conservation algorithms.…"

Supplementary file 1_Genetic analysis of non-syndromic peg lateralis using whole-exome sequencing.docx حسب Junglim Choi (22045838)

"…In-silico mutation impact analysis was performed using Polymorphism Phenotyping v2, sorting intolerant from the tolerant, and integrated score of co-evolution and conservation algorithms.…"

IoT Network Intrusion Dataset حسب Qusay H. Mahmoud (21419838)

"…New techniques and detection algorithms required a well-designed dataset for IoT networks. …"

Confusion matrix of the model. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

Results of the selected model training. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

Dataset-specific category data. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

Transfer learning. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

The overview of LostNet. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

The overview of CBAM. حسب Meihua Zhou (12331454)

"…A photo matching network is proposed, integrating the transfer learning capabilities of MobileNetV2 with the Convolutional Block Attention Module (CBAM) and utilizing perceptual hashing algorithms for their simplicity and speed. …"

Clinical Characteristics of Patients. حسب Yifei Wang (95207)

"…</p><p>Results</p><p>Through univariate and multivariate Cox regression analyses, we identified seven independent risk factors associated with the survival of RSC patients: age (HR = 1.9, 95% CI: 1.3-2.8, P = 0.001), gender (HR = 0.6, 95% CI: 0.4-0.9, P = 0.013), diabetes (HR = 2.0, 95% CI: 1.3-3.1, P = 0.002), tumor differentiation (HR = 2.1, 95% CI: 1.4-3.1, P < 0.001), tumor N stage (HR = 2.02, 95% CI: 1.2-3.4, P = 0.009), distant metastasis (HR = 4.2, 95% CI: 2.7-6.7, P < 0.001), and anastomotic leakage (HR = 2.4, 95% CI: 1.1-5.3, P = 0.034). …"

Patient screening information for this study. حسب Yifei Wang (95207)

"…</p><p>Results</p><p>Through univariate and multivariate Cox regression analyses, we identified seven independent risk factors associated with the survival of RSC patients: age (HR = 1.9, 95% CI: 1.3-2.8, P = 0.001), gender (HR = 0.6, 95% CI: 0.4-0.9, P = 0.013), diabetes (HR = 2.0, 95% CI: 1.3-3.1, P = 0.002), tumor differentiation (HR = 2.1, 95% CI: 1.4-3.1, P < 0.001), tumor N stage (HR = 2.02, 95% CI: 1.2-3.4, P = 0.009), distant metastasis (HR = 4.2, 95% CI: 2.7-6.7, P < 0.001), and anastomotic leakage (HR = 2.4, 95% CI: 1.1-5.3, P = 0.034). …"

Data Sheet 1_Dataset of date palm tree (Phoenix dactylifera L.) thermal images and their classification based on Red Palm Weevil (Rhynchophorus ferrugineus) infestation.pdf حسب Adnan Nadeem (21633818)

"…This dataset aims to facilitate (1) RPW pest management and (2) the development and evaluation of machine learning algorithms for automated date palm tree classification by providing a diverse collection of images and groundtruth labels. …"

Addressing the Gap in Oncologist Training حسب Skylar Gay (20696057)

"…An automated “geometry-aware convolution” technique was developed to create suboptimal dose distributions with (1) decreased organs-at risk sparing (10%-60% increase in Dmean) or (2) decreased target conformality (5%-10% decrease in V95%). …"

Image 1_Triglyceride–glucose index as a key predictor of ARDS in acute pancreatitis: SHAP analysis reveals its critical role in risk stratification.pdf حسب Ju Luo (3233037)

"…The XGBoost (AUC = 0.857 ± 0.034) and Random Forest (AUC = 0.851 ± 0.045) algorithms were the best two performance methods. In the SHAP analysis, TyG was the second most important feature in the RF model and the seventh in the XGBoost model.…"