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1961
The role of novel risk-scoring systems in predicting the efficacy of immunotherapy
Published 2025-02-01“…However, some patients resist ICIs, highlighting the need for novel risk-scoring systems to predict immunotherapy efficacy. Purpose – to evaluate the Lung Immune Prognostic Index (LIPI), Advanced Lung Cancer Inflammation Index (ALI), Patras Immunotherapy Score (PIOS), Prognostic Nutritional Index (PNI), and LEM score (Leukocytes, ECOG, Metastases) as predictors of ICI therapy efficacy in patients with mNSCLC. …”
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1962
Prediction of acute pancreatitis severity based on early CT radiomics
Published 2024-11-01“…Abstract Background This study aims to develop and validate an integrated predictive model combining CT radiomics and clinical parameters for early assessment of acute pancreatitis severity. …”
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1963
Risk Prediction Models for Perioperative Hypothermia: A Systematic Review
Published 2025-07-01“…Due to its significant impact, this study systematically reviews and evaluates existing risk prediction models for perioperative hypothermia. …”
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1964
Deformation prediction in innovative implant design with machine learning approaches
Published 2025-09-01“…Unlike classic implants, the sleeved implant is predicted to provide a more homogeneous distribution of chewing forces on the bone by reducing stress concentrations around the implant. …”
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1965
Prediction of Recurrence of Atrial Fibrillation After Radiofrequency Ablation by Frailty
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1966
Bayesian network for predicting mandibular third molar extraction difficulty
Published 2025-01-01“…Abstract Background This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient’s personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications. …”
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1967
Slope deformation prediction based on GA–BP neural networks
Published 2025-04-01“…Traditionally, empirical methods and numerical simulations have been employed to predict slope displacement. …”
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Article -
1968
Interpretable machine learning for predicting isolated basal septal hypertrophy.
Published 2025-01-01“…<h4>Objective</h4>To evaluate the effectiveness of five machine learning algorithms in predicting thickening of the basal segment of the interventricular septum and to develop a simple, yet efficient, prediction model for BSH.…”
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1969
Genomic Landscape and Prediction of Udder Traits in Saanen Dairy Goats
Published 2025-01-01“…Genome-wide association studies (GWAS) revealed four candidate genes with selection signatures linked to udder traits. Predictive models, including GBLUP, kernel ridge regression (KRR), and Adaboost.RT, were evaluated for genomic estimated breeding value (GEBV) prediction. …”
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1970
Comparison of Risk Assessment Models for Predicting Postpartum Venous Thromboembolism
Published 2025-05-01“…Methods: This retrospective study was conducted from February 2019 to February 2024. …”
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Article -
1971
Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma
Published 2025-01-01“…This study explores the utility of radiogenomics and machine learning (ML) in predicting these oncogenic signaling pathways in GBM patients. …”
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Article -
1972
Collagen turnover biomarkers to predict outcome of patients with biliary cancer
Published 2025-02-01“…The diagnostic and prognostic value of the markers was evaluated for overall survival (OS) and progression-free survival (PFS). …”
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Article -
1973
Change in elevation predicts 100 km ultra marathon performance
Published 2025-07-01“…A total of 858,544 race records (732,748 from men and 125,796 from women) from 317,312 unique runners originating from 103 different countries and participating in 2,648 100-km races held in 80 different countries worldwide between 1892 and 2022 were analyzed using several descriptive, inferential and predictive methods, including a machine learning XG Boost Regression model. …”
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Article -
1974
Machine Learning for Non-Destructive Prediction of Sunflower Leaf Area
Published 2025-01-01“…However, its measurement using traditional methods can be limited. The search for non-destructive approaches based on leaf dimensions is essential, and machine learning offers promising alternatives for accurate estimation. …”
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Article -
1975
Assessing sepsis-induced immunosuppression to predict positive blood cultures
Published 2024-11-01“…This study proposes a novel strategy to predict positive blood cultures by assessing sepsis-induced immunosuppression status through endotoxin tolerance assessment.MethodsOptimal assay conditions have been explored and tested in sepsis-suspected patients meeting the Sepsis-3 criteria. …”
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1976
Plasma proteomic signature for preoperative prediction of microvascular invasion in HCC
Published 2025-09-01“…However, reliable non-invasive biomarkers for the preoperative evaluation and diagnosis of MVI are urgently needed in clinical practice. …”
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Article -
1977
The Predictive Role of StrainParameters in Predicting All-Cause Mortality in Diabetic Hypertensive Patients with Normal Left Ventricular Systolic Function in Long-Term Follow-up
Published 2025-03-01“…In right ventricular strain evaluation, four-chamber right ventricular strain (RV4CSL%) (26.1±5.4 vs. 20.8±6.2, p-value: 0.005) was also worse in the mortality group. …”
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1978
Comparison of Classical Arima Forecasting Methods to the Machine Learning LSTM Method: a Case Study on DAX® 50 ESG Index
Published 2025-06-01“…Predictive accuracy is measured by standard error metrics (MAE, RMSE, MAPE) and the Diebold-Mariano test. …”
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1979
Novel metabolic prognostic score for predicting survival in patients with cancer
Published 2025-01-01“…The Kaplan–Meier method was used to evaluate the survival of patients with varying burdens of metabolic disorders. …”
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Article -
1980
Can Phonemic Verbal Fluency Be Used to Predict Alzheimer’s Disease?
Published 2024-11-01“…Method: A verbal fluency task was administered to 25 patients with MCI and their respective control subjects. …”
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