Enhancing Power Grid Reliability With Machine Learning and Auxiliary Classifier Generative Adversarial Networks: A Study on Fault Detection Using the Georgia Electric System Load D... by Hafeez Ur Rehman Siddiqui, Robert Brown, Adil Ali Saleem, Muhammad Amjad Raza, Sandra Dudley

“…A comparative evaluation of models including Decision Trees (DT), Random Forest (RF), Extra Tree Classifier (ETC), Gradient Boosting Classifier (GBC), and K-Nearest Neighbors (KNN) revealed the Extra Tree Classifier achieved the highest testing accuracy of 93.85%. …”
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Identification of a New Prognostic Risk Signature of Clear Cell Renal Cell Carcinoma Based on N6-Methyladenosine RNA Methylation Regulators by Yan Zhang, Yao Yao, Xiaochen Qi, Jianyi Li, Meihong Liu, Xiangyu Che, Yingkun Xu, Guangzhen Wu

“…Then, we internally validated this signature by random sampling. Finally, we explored the role of the genes in the signature in some common pathways. …”
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Patient perspectives and utilization of telemedicine for chronic conditions in Pakistan barriers and facilitators towards its access by Muhammad Muzzamil, Mahek Karim, Sara Saeed Khurram, Iffat Zafar Aga, Shahkamal Hashmi, Hina Gul Hassan, Yasha Younus

“…These participants were initially identified by Electronic Health Records (EHR) of Sehat Kahani and subsequently registered following randomization through systematic random sampling. Results This study investigated telemedicine perceptions among 450 chronic disease patients (74.2% female, avg. age 40.6). …”
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A journey into a Mediterranean diet and type 2 diabetes: a systematic review with meta-analyses by Demosthenes Panagiotakos, Katherine Esposito, Paolo Chiodini, Maria Ida Maiorino, Giuseppe Bellastella, Dario Giugliano

“…Trials were included for meta-analyses if they had a control group treated with another diet, if they were of sufficient duration (at least 6 months), and if they had at least 30 participants in each arm. A random-effect model was used to pool data.Participants Adults with or at risk for type 2 diabetes.Interventions Dietary patterns that described themselves as using a ‘Mediterranean’ dietary pattern.Outcome measures The outcomes were glycaemic control, cardiovascular risk factors and remission from the metabolic syndrome.Results From 2824 studies, 8 meta-analyses and 5 RCTs were eligible. …”
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Molecular-genetic mechanisms of the interaction between processes of cell response to mechanical stress and neuronal apoptosis in primary open-angle glaucoma by O. V. Saik, N. A. Konovalova, P. S. Demenkov, N. V. Ivanisenko, T. V. Ivanisenko, D. E. Ivanoshchuk, O. S. Konovalova, O. A. Podkolodnaya, I. N. Lavrik, N. A. Kolchanov, V. A. Ivanisenko

“…It was shown that genes associated with POAG are statistically significantly more often represented among the genes involved in the interactions between CRMS and neuronal apoptosis than it was expected by random reasons, which can be an explanation for the effect of POAG leading to the retinal ganglion cell death.…”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Experimental results demonstrate that ACGNN yields significant path planning outcomes on both public and custom-built datasets, surpassing the traditional Dijkstra’s shortest path algorithm, random graph network (RGN), and conventional GNN methodologies. …”
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Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies by Da Yao, Qing Chang, Qi-Jun Wu, Shan-Yan Gao, Huan Zhao, Ya-Shu Liu, Yu-Ting Jiang, Yu-Hong Zhao

“…Abdominal subcutaneous fat thickness, waist circumference, waist-hip ratio or body fat distribution were elected as measures of maternal central obesity, and all diagnostic criteria for GDM were accepted. The random effect meta-analysis was performed to evaluate the relationship between central obesity and the risk of GDM. …”
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Characterization of Complex Image Spatial Structures Based on Symmetrical Weibull Distribution Model for Texture Pattern Classification by Jinping Liu, Jiezhou He, Zhaohui Tang, Pengfei Xu, Wuxia Zhang, Weihua Gui

“…Visually, the visual appearance of the complex spatial structure (CSS) of texture pattern (TP) generally depends on the random organization (or layout) of local homogeneous fragments (LHFs) in the imaged surface. …”
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Therapeutic Adherence in Hypertensive Patients of the Guanabacoa Julio Antonio Mella University Polyclinic by Addys Díaz Piñera, Armando Rodríguez Salvá, Milenia León Sánchez, Lisbeth Fernández González, Armando Humberto Seuc Jo, Nelsy Álvarez Mesa

“…<br /><strong>Methods:</strong> a descriptive cross-sectional study was carried out in the previously mentioned area between September and December 2019. Simple random sampling was used. 337 hypertensive people older than 35 years were studied. …”
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Prevalence of nutritional anemia and its risk factors in children under five in the Gaza Strip by Abdel Hamid El Bilbeisi, Abdel Hamid El Bilbeisi

“…A total of 750 children, aged 24–59 months, were selected from all Gaza Strip governorates, using a cluster random sampling method. Children and their parents were assessed using an interview-based questionnaire, anthropometric measurements, biochemical measurements, and clinical examination. …”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). …”
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Predicted quality benefits of achievable performance benchmarks of chronic heart failure care in China: results from a nationwide observational study by Xi Li, Chao Wang, Jingkun Li, Yupeng Wang, Xiaoqiang Bao, Meina Liu, Qiuju Zhang, Chang Yin, Xudong Ma

“…Objectives This study aimed to set a data-driven achievable performance benchmark, explore the process–outcome association and speculate about the net gain in quality improvement with benchmarking.Design Observational study.Setting Patient survey conducted at 466 secondary and tertiary hospitals across 31 provinces, autonomous regions and municipalities in China.Participants 183 334 patients diagnosed with chronic heart failure (CHF) who were treated at 466 Chinese hospitals from January 2011 through May 2017.Primary independent variables Hospital process composite performance (HPCP).Secondary independent variables Patient-level and hospital-level characteristics.Primary outcome measure Patients getting better or recovered after treatment, in-hospital mortality, length of hospital stay (LOS) and medical cost.Methods HPCP was calculated using denominator-based weights. Mixed random-intercept models were used to evaluate the contributions of HPCP on patient outcomes and to speculate quality improvement after adjusting HPCP to benchmark level.Results When all hospitals were to operate at the benchmark level, the proportion of patients getting better or recovered after treatment would increase in most hospitals, particularly those with low baseline rates. …”
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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. …”
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Comparison of the efficacy of seven non-surgical methods combined with mechanical debridement in peri-implantitis and peri-implant mucositis: A network meta-analysis. by Yingjie Bai, Shengao Qin, Bingshuai Lu, Weiyi Wang, Guowu Ma

“…We employed a frequency random effects network meta-analysis model to combine the effect sizes of the trials using standardized mean difference (SMD) and 95% confidence intervals (CIs). …”
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Examining tolerability, safety, and blinding in 1032 transcranial electrical stimulation sessions for children and adolescents with neuropsychiatric and neurodevelopmental disorder... by Andrea Battisti, Giulia Lazzaro, Luciana Ursumando, Barbara D’Aiello, Valeria Zanna, Floriana Costanzo, Stefano Vicari, Deny Menghini

“…Abstract The present study first extensively evaluated the tolerability, safety, and blinding of transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS) in paediatric clinical populations, composed of 92 children and adolescents (54 females, age range: 8–17 years), involving 1032 sessions across neuropsychiatric (i.e., anorexia nervosa) and neurodevelopmental (i.e., attention deficit and hyperactivity disorder, developmental dyscalculia) conditions. …”
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Swasthya Pahal (Health for All) Using a Sustainable, Multisector, Accessible, Affordable, Reimbursable, and Tailored Informatics Framework in Rural and Urban Areas of Chennai, Tami... by Ashish Joshi, Krishna Mohan Surapaneni, Ashoo Grover, Harpreet Kaur, Sofia Rani Saggu, Doilyn Oliveira

“…Objective assessments such as weight, blood pressure, and random blood sugar levels will be measured. In addition, the usefulness, acceptance, and effectiveness of the Swasthya Pahal program will be determined. …”
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An epidemiological assessment of health status among a cohort of tuberculosis survivors: prospective research in a western Indian city by Venu Shah, Viral Dave, Vaidehi Gohil, Hardika Khanpara

“…As per the calculated sample size, 180 study participants were recruited by systematic random sampling from a list of cured TB cases from July to September 2021. …”
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Prevalence of Depressive Symptoms and Associated Factors among HIV-Positive Youth Attending ART Follow-Up in Addis Ababa, Ethiopia by Helina Abebe, Shegaye Shumet, Zebiba Nassir, Melkamu Agidew, Dessie Abebaw

“…In a cross sectional study, 507 HIV-positive young people from public health hospitals were recruited by systematic random sampling technique. Beck Depression Inventory-II was used to assess depressive symptoms. …”
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A data-driven approach to study temporal characteristics of COVID-19 infection and death Time Series for twelve countries across six continents by Sabyasachi Guharay

“…These changes can be attributed to the underlying dynamics of state transitions, especially from a random state to either mean-reversion or long-range memory/persistence states. …”
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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…Multinomial Naïve Bayes (MNB), Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF), and Decision Integration Strategy (DIS) are evaluated as conventional machine learning algorithms. …”
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