One advantage of our algorithm is that it is not binary in nature. حسب Yong Kuk Kim (13955214)

A new fast filtering algorithm for a 3D point cloud based on RGB-D information حسب Chaochuan Jia (7256237)

Machine learning and an angiogenesis signature with prognostic power. حسب Rodrigo Guarischi-Sousa (8138166)

Table_1_Deep learning models for predicting the survival of patients with chondrosarcoma based on a surveillance, epidemiology, and end results analysis.docx حسب Lizhao Yan (11774354)

"…Several prognostic models have been created utilizing multivariate Cox regression or binary classification-based machine learning approaches to predict the 3- and 5-year survival of patients with chondrosarcoma, but few studies have investigated the results of combining deep learning with time-to-event prediction. …"

DataSheet_1_Accurate Tumor Delineation vs. Rough Volume of Interest Analysis for 18F-FDG PET/CT Radiomics-Based Prognostic Modeling inNon-Small Cell Lung Cancer.docx حسب Shima Sepehri (11574997)

"…Logistic regression (LR), random forest (RF), and support vector machine (SVM), as well as their consensus through averaging the output probabilities, were considered for feature selection and modeling for overall survival (OS) prediction as a binary classification (either median OS or 6 months OS). …"

Development and validation of the GSRS. حسب Yu Zhang (12946)

Image_2_Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome.JPEG حسب Yiguo Liu (12478320)

"…The prognostic variables used to develop the nomogram were identified based on a forward stepwise binary logistic regression, and the predictive ability of the nomogram was evaluated by the areas under the receiver operating characteristic curve (AUC) and the calibration curve. …"

Image_1_Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome.JPEG حسب Yiguo Liu (12478320)

"…The prognostic variables used to develop the nomogram were identified based on a forward stepwise binary logistic regression, and the predictive ability of the nomogram was evaluated by the areas under the receiver operating characteristic curve (AUC) and the calibration curve. …"

Table_1_Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome.DOCX حسب Yiguo Liu (12478320)

"…The prognostic variables used to develop the nomogram were identified based on a forward stepwise binary logistic regression, and the predictive ability of the nomogram was evaluated by the areas under the receiver operating characteristic curve (AUC) and the calibration curve. …"

Image_4_Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome.JPEG حسب Yiguo Liu (12478320)

"…The prognostic variables used to develop the nomogram were identified based on a forward stepwise binary logistic regression, and the predictive ability of the nomogram was evaluated by the areas under the receiver operating characteristic curve (AUC) and the calibration curve. …"

Image_3_Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome.JPEG حسب Yiguo Liu (12478320)

"…The prognostic variables used to develop the nomogram were identified based on a forward stepwise binary logistic regression, and the predictive ability of the nomogram was evaluated by the areas under the receiver operating characteristic curve (AUC) and the calibration curve. …"

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease حسب Zhuoyan Chen (12193358)

"…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …"

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

"…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles حسب Soham Savarkar (21811825)

"…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …"