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  1. 37201
    por Vibert, Bethany, Segura, Patricia, Gallagher, Louise, Georgiades, Stelios, Pervanidou, Panagiota, Thurm, Audrey, Alexander, Lindsay, Anagnostou, Evdokia, Aoki, Yuta, Birken, Catherine S., Bishop, Somer L., Boi, Jessica, Bravaccio, Carmela, Brentani, Helena, Canevini, Paola, Carta, Alessandra, Charach, Alice, Costantino, Antonella, Cost, Katherine T., Cravo, Elaine A, Crosbie, Jennifer, Davico, Chiara, Donno, Federica, Fujino, Junya, Gabellone, Alessandra, Geyer, Cristiane T, Hirota, Tomoya, Kanne, Stephen, Kawashima, Makiko, Kelley, Elizabeth, Kim, Hosanna, Kim, Young Shin, Kim, So Hyun, Korczak, Daphne J., Lai, Meng-Chuan, Margari, Lucia, Marzulli, Lucia, Masi, Gabriele, Mazzone, Luigi, McGrath, Jane, Monga, Suneeta, Morosini, Paola, Nakajima, Shinichiro, Narzisi, Antonio, Nicolson, Rob, Nikolaidis, Aki, Noda, Yoshihiro, Nowell, Kerri, Polizzi, Miriam, Portolese, Joana, Riccio, Maria Pia, Saito, Manabu, Schwartz, Ida, Simhal, Anish K., Siracusano, Martina, Sotgiu, Stefano, Stroud, Jacob, Sumiya, Fernando, Tachibana, Yoshiyuki, Takahashi, Nicole, Takahashi, Riina, Tamon, Hiroki, Tancredi, Raffaella, Vitiello, Benedetto, Zuddas, Alessandro, Leventhal, Bennett, Merikangas, Kathleen, Milham, Michael P., Di Martino, Adriana
    Publicado 2023
    “…To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups. …”
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    CRISIS AFAR: an international collaborative study of the impact of the COVID-19 pandemic on mental health and service access in youth with autism and neurodevelopmental conditions
  2. 37202
    “…Six different machine learning classifiers were applied: random forest (RF), K-nearest neighbor (KNN), Gaussian Naive Bayes, decision tree, logistic regression, and support vector machine (SVM). …”
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    A radiomics model based on aortic computed tomography angiography: the impact on predicting the prognosis of patients with aortic intramural hematoma (IMH)
  3. 37203
    “…Three machine learning algorithms, support vector machine-recursive feature elimination (SVM-RFE), random forest (RF), and least absolute shrinkage and selection operator (LASSO), were applied to determine characteristic genes, which were verified by ROC curve analysis and immunohistochemistry (IHC) using clinical samples. …”
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    Integrated multiple microarray studies by robust rank aggregation to identify immune-associated biomarkers in Crohn's disease based on three machine learning methods
  4. 37204
    “…Principal components analysis and hierarchical clustering analysis were performed to study samples distribution and random forest (RF) algorithms were computed for the classification task. …”
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    A study of differential microRNA expression profile in migraine: the microMIG exploratory study
  5. 37205
    “…The explainable ML model based on Random Forest (RF) algorithm was developed and modified on training cohort, and tested on testing cohort. …”
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    Explainable machine learning model reveals its decision-making process in identifying patients with paroxysmal atrial fibrillation at high risk for recurrence after catheter ablation
  6. 37206
    “…TRIAL REGISTRATION: : This study is being conducted in accordance with the tenets of the Helsinki Declaration, and has been approved by the central institutional review board (IRB) of Wake Forest University Health Sciences (approval number: 00069593) and local IRB of each participating clinical center; and was registered on Nov 27, 2020, at ClinicalTrials.gov (NCT04646226). …”
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    Study protocol of a randomized controlled trial of fistula vs. graft arteriovenous vascular access in older adults with end-stage kidney disease on hemodialysis: the AV access trial
  7. 37207
    “…The present meta-analysis was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement using R software 4.1.3 to create forest plots. Q statistics and the I(2) index were used to evaluate heterogeneity in this meta-analysis. …”
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    Post-acute COVID-19 symptom risk in hospitalized and non-hospitalized COVID-19 survivors: A systematic review and meta-analysis
  8. 37208
    “…Next, we analysed the prognostic indices by multivariate Cox proportional hazard regression (1) by using either significant (p < 0.05) or borderline significant (p = 0.05–0.10) indices in the univariate analysis (first multivariate analysis) or (2) by using the selected features with random forest algorithms (second multivariate analysis). …”
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    Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features
  9. 37209
    por Chang, Donghua, Wang, Qin
    Publicado 2023
    “…RevMan 5.3 software was used to draw a risk bias map, and Stata 16.0 was used to plot a sensitivity and specificity forest map. A summary receiver operating characteristics (SROC) curve was plotted, and the area under the curve (AUC) was calculated. …”
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    Diagnostic value of ultrasound elastography and conventional ultrasound for thyroid nodules: a meta-analysis
  10. 37210
    “…In this study, various machine learning algorithms were used (random forest, RF; convolutional neural networks, CNN; extreme gradient boosting, XGBoost; ElasticNetCV; Bayesian Ridge; and particle swarm optimization-support vector regression) to select the most suitable algorithm for predicting and comparing the quality of potential source rocks. …”
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    Hydrocarbon Generation from Low-Mature Saline Lacustrine Sediments Studied Using Machine Learning and Chemometric Methods: The Succession of the Sikeshu Sag, Junggar Basin, NW China
  11. 37211
    “…In the VAS score group, PRP outperformed hyaluronic acid (HA) (WMD 1.3, 95% CI 0.55–2.55) and corticosteroids (CS) (WMD 4.85, 95% CI 4.02–5.08), according to the forest map results. PRP also outperformed CS (WMD 14.76, 95% CI 12.11–17.41), ozone (WMD 9.16, 95% CI 6.89–11.43), and PRP + HA (WMD 2.18, 95% CI 0.55–3.81) in the WOMAC total score group. …”
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    A comparative study of the efficacy of intra-articular injection of different drugs in the treatment of mild to moderate knee osteoarthritis: A network meta-analysis
  12. 37212
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    Viral predation pressure on coral reefs
  13. 37213
    “…DISCUSSION: The study indicated that tree growth-climate response models could help deeply understand the impact of climate change on tree growth adaptation and would be beneficial for developing sustainable management policies for forest ecosystems in the transition zone from warm-temperate to subtropical climates.…”
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    Dendroclimatic response of Pinus tabuliformis Carr. along an altitudinal gradient in the warm temperate region of China
  14. 37214
    “…Machine‐learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver‐operating characteristic curve (AUC). …”
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    Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic‐ischemic encephalopathy
  15. 37215
    “…We also aimed to assess the performance of hybrid versions of these models that incorporated additional predictors generated by 2 clustering algorithms, hierarchical density-based spatial clustering of applications with noise (HDBSCAN) and unsupervised random forest (uRF). METHODS: We constructed a supervised machine learning model based on XGBoost and unsupervised models based on HDBSCAN and uRF. …”
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    Predicting Measles Outbreaks in the United States: Evaluation of Machine Learning Approaches
  16. 37216
    “…Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. …”
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    Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019
  17. 37217
    por Martinez, Caroline, Chen, Zhe Sage
    Publicado 2023
    “…Machine learning models including the Logistic Regression (LR) classifier, Support Vector Machine (SVM), and Random Forest (RF) model were trained using these features. …”
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    Identification of atypical sleep microarchitecture biomarkers in children with autism spectrum disorder
  18. 37218
    por Sun, Lin-xi, Li, Yuan-yuan, Xie, Yan-ming
    Publicado 2023
    “…The results of Meta-analysis were represented by forest plots. RESULTS: A total of 8 studies were included involving a total sample size of 656 cases. …”
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    Efficacy and safety of Tongmai Jiangtang capsule combined with conventional therapy in the treatment of diabetic peripheral neuropathy: a systematic review and meta-analysis
  19. 37219
    “…We conducted stepwise regression to filter the most important anthropometric measurements and performed a multiple mediation analysis to test whether the selected anthropometric measurements had mediation effects on the total effect of the DASH diet on hypertension. Random forest models were conducted to identify nutrient subsets associated with the DASH score and anthropometric measurements. …”
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    Waist-to-Height Ratio Is a Stronger Mediator in the Association between DASH Diet and Hypertension: Potential Micro/Macro Nutrients Intake Pathways
  20. 37220
    “…Heterogeneity was assessed via Forest plots. FINDINGS: The two RCTs included 286 patients. …”
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    Intraarrest transport, extracorporeal cardiopulmonary resuscitation, and early invasive management in refractory out-of-hospital cardiac arrest: an individual patient data pooled analysis of two randomised trials
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