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Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer
Published 2025-04-01“…This study sought to investigate the significance of ICD in CESC and to establish an ICDRs prognostic model to improve immunotherapy efficacy for patients with cervical cancer.MethodsICD-associated genes were screened at the single-cell and transcriptome levels based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network (WGCNA) analysis. …”
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122
Melanoma risk prediction models
Published 2014-01-01“…A continuous melanoma database growth would provide for further adjustments and enhancements in model accuracy as well as offering a possibility for successful application of more advanced data mining algorithms.…”
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123
Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data
Published 2025-06-01“…We hypothesize that a combination of intake screening PAU and the ML model will be the optimal approach, in that the combination will be more accurate and can have practical application in this context. …”
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Machine Learning Model for Early Detection of COVID-19 by Heart Rhythm Abnormalities
Published 2023-07-01“…The work aims at creating a mathematical model based on machine learning algorithms to automate the process of detecting covid abnormalities in the heart rhythm. …”
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Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics
Published 2025-03-01“…This study aimed to explore the feasibility of utilising machine learning models to accurately screen for MASLD in large populations based on a combination of essential demographic and clinical characteristics. …”
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127
Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study
Published 2025-04-01“…The ML algorithms implemented in this study include the k-nearest neighbors algorithm, random forest ML algorithms, multilayer perceptron artificial neural network, logistic regression models, gradient boosting classifier, and linear support vector machine classifier. …”
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128
Joint Decision-Making Model Based on Consensus Modeling Technology for the Prediction of Drug-Induced Liver Injury
Published 2021-01-01“…Submodels for each consensus model were obtained through joint optimization. The parameters and features of each submodel were optimized jointly based on the hybrid quantum particle swarm optimization (HQPSO) algorithm. …”
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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity...
Published 2025-06-01“…ObjectiveThis study aims to evaluate the potential association between the four-variable screening tool (the 4 V) potential predictive model in predicting coronary artery disease (CAD) risk in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) and its correlation with the severity of coronary atherosclerosis, as measured by the Gensini scoring system.Methods1197 OSAHS patients with suspected CAD who were hospitalized in the First Affiliated Hospital of Xinjiang Medical University between March 2020 and February 2024 were selected. …”
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131
Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury
Published 2024-12-01“…Ensemble stepwise feature selection method was used to screen for effective features. The prediction models of short-term mortality were developed by seven machine learning algorithms. …”
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132
Molecular Docking: Methodological Approaches of Risk Assessment
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133
Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis
Published 2025-06-01“…Using the SNR as the evaluation metric, the algorithm performs data screening on the replay buffer parameters before training the deep network for predicting coupled neuron model performance. …”
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134
Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical...
Published 2025-08-01“…The backward LR method and seven ML algorithms were applied to train and test the prediction models. …”
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Study Design and Rationale for the PHINDER Study: Pulmonary Hypertension Screening in Patients with Interstitial Lung Disease for Earlier Detection
Published 2025-07-01“…Planned Outcomes Following study completion, statistical tools will be used to derive a practical model for a screening algorithm using the variables identified in the study as most predictive of PH in patients with ILD. …”
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A Blockchain Solution for the Internet of Vehicles with Better Filtering and Adaptive Capabilities
Published 2025-02-01“…To solve this problem, we propose a gradually accelerating environment adaptive consensus algorithm, AE-PBFT, that can be applied to IoV. It includes a trust management model that achieves gradual acceleration by recording the historical continuous behavior of nodes, thereby improving the efficiency of screening nodes with different intentions, accelerating the consensus process, and reducing latency. …”
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GIS vibration signal denoising algorithm based on SVD-IACMD
Published 2024-11-01“…In response to the current situation, an on-site vibration signal denoising diagnosis algorithm based on the singular value decomposition (SVD)-improve adaptive chirp mode decomposition (IACMD) algorithm is proposed. …”
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138
Research of color models in digital graphics
Published 2024-12-01“…The study focuses on a detailed examination of the RGB, CMYK, HSL/HSV, and LAB color models. It is established that the RGB model is an additive system optimized for screens and displays, as it provides a broad and vibrant color range suitable for digital applications. …”
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COMPUTER- AIDED MODELING AND IMPROVING OF RISOGRAPH PRINTING
Published 2014-12-01“…The considered improvement of qualit y of the risofraph print based on a mathematical model in the environment Matlab by using the specialized algorithms and digital filter of the Image Processing Toolbox. …”
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