Image_4_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

Image_5_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

Image_3_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

Image_1_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

Image_2_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangio... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

DATASET AI حسب Elena Stamate (18836305)

"…</p><p dir="ltr">The primary aim of this dataset is to enable the development and validation of machine learning models for:</p><ul><li>Early identification of STEMI patients at high risk of developing cardiogenic shock;</li><li>Clinical triage optimization and prioritization for urgent angiography;</li><li>Supporting time-sensitive decision-making in resource-limited or overcrowded emergency settings.…"

PGAE-ICA_A simplified digital system for intellectual measurement-assessment in children and adolescents using cognitive testing and machine learning techniques حسب Runzhou Wang (5894849)

"…To date, there is no digital and simplified tool specifically designed to evaluate whether intelligence is normal or abnormal in these age stages. The present study aims to develop an intelligence measurement-assessment system based on primary cognitive ability tests across four cognitive domains and a machine learning model to distinguish between normal and abnormal intelligence. …"

DataSheet_1_Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal chola... حسب Di Wang (329735)

"…Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). …"

Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx حسب Xiaotong Sun (6535064)

"…Family migration brings about changes in urban integration costs and benefits, affecting health investment.</p>Objective<p>The primary objective of this research is to investigate the influence of urban integration of migrant workers' families on their mental wellbeing, with the aim of offering policy recommendations conducive to the realization of a comprehensive public health strategy in China.…"

DataSheet_1_A machine learning model based on ultrasound image features to assess the risk of sentinel lymph node metastasis in breast cancer patients: Applications of scikit-learn... حسب Gaosen Zhang (539619)

"…Background<p>This study aimed to determine an optimal machine learning (ML) model for evaluating the preoperative diagnostic value of ultrasound signs of breast cancer lesions for sentinel lymph node (SLN) status.…"

Data_Sheet_1_Tobacco shred varieties classification using Multi-Scale-X-ResNet network and machine vision.docx حسب Qunfeng Niu (13263975)

"…ResNet50 is used as the primary classification and recognition network structure. …"

LCLU location-allocation with spatial contiguity and compactness حسب Sitarani Safitri (18129556)

"…In 2022, Indonesia, in general, and Java, in particular, already experienced a biocapacity deficit based on a study by the Global Footprint Network. This study aims to optimize land cover/land use (LCLU) location selection. …"

Datasheet1_An explainable machine learning approach using contemporary UNOS data to identify patients who fail to bridge to heart transplantation.pdf حسب Mamoun T. Mardini (14672933)

"…We used the eXtreme Gradient Boosting (XGBoost) algorithm to build and validate ML models. We developed two models: (1) a comprehensive model that included all patients in our cohort and (2) separate models designed for each of the 11 UNOS regions.…"

Special Education Demand Prediction Database in Peru Using Machine Learning حسب Raúl Garcia (18938521)

"…The demand-predictive approach allows for the identification of nonlinear and dynamic growth patterns at different educational levels (0–2 years, Preschool and Primary) across the country's regions. The models achieved high accuracy rates (R² > 0.97), with performance metrics including a root mean square error (RMSE) below 190, a mean absolute error (MAE) below 70, and a mean absolute percentage error (MAPE) below 10%, demonstrating their usefulness as a strategic support tool for decision-making, optimizing the planning of economic and financial resources for special education. …"

Heat and mass transfer analysis for bi-dimensional bioconvective MHD nanofluid with varying thermal traits حسب Dil Awaiz Kanwal (18697899)

"…The primary objective of the investigation is to optimize the thermal energy transfer efficiency of the fluid while concurrently minimizing associated costs, with the secondary aim of diminishing the frictional resistance at the fluid-solid interface. …"

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

"…</p>Methods<p>This retrospective observational cohort study used data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The primary outcome was incidence of delirium. Feature importance of BSS was initially assessed using a machine learning algorithm, while restricted cubic spline (RCS) models and multivariable logistic analysis evaluated the relationship between BSS and delirium. …"

DataSheet_1_Prediction of Response to Induction Chemotherapy Plus Concurrent Chemoradiotherapy for Nasopharyngeal Carcinoma Based on MRI Radiomics and Delta Radiomics: A Two-Center... حسب Yuzhen Xi (12445899)

"…Objective<p>We aimed to establish an MRI radiomics model and a Delta radiomics model to predict tumor retraction after induction chemotherapy (IC) combined with concurrent chemoradiotherapy (CCRT) for primary nasopharyngeal carcinoma (NPC) in non-endemic areas and to validate its efficacy.…"

Image 4_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.pdf حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Image 1_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.tif حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"

Image 7_Integrative single-cell and exosomal multi-omics uncovers SCNN1A and EFNA1 as non-invasive biomarkers and drivers of ovarian cancer metastasis.tif حسب Liping Tang (77094)

"…We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. …"