Meta Analysis of Clustering Nursing for Stroke Associated Pneumonia by Chunyan HAN, Cun ZHAO, Xinglei WANG, Yali CHANG, Li YAO, Yihong KE, Jinhui TIAN, Xinman DOU

“…The trials (RCTs) included randomized controlled was about clustering nursing intervention for stroke-related pneumonia. …”
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Profile of postpartum patients with urinary retention at Koja Regional Hospital, Jakarta, Indonesia by Suskhan Djusad, Alfa Putri Meutia, Surahman Hakim

“…Results: Out of 300 subjects selected through consecutive random sampling, 63.7% experienced PPUR, while 36.3% had normal urinary function. …”
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Effects of Simultaneously Performed Dual-Task Training with Aerobic Exercise and Working Memory Training on Cognitive Functions and Neural Systems in the Elderly by Hikaru Takeuchi, Daniele Magistro, Yuka Kotozaki, Kosuke Motoki, Keyvan Kashkouli Nejad, Rui Nouchi, Hyeonjeong Jeong, Chiho Sato, Salvatore Sessa, Ryoichi Nagatomi, Massimiliano Zecca, Atsuo Takanishi, Ryuta Kawashima

“…Older adults (65.9±13.7 years old) participated in 3 months of SDAEWMT, WMT, or AET after random allocation, and the effects of SDAEWMT were compared with those of WMT and AET. …”
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Circulating Levels of Glial Cell Line-Derived Neurotrophic Factor (GDNF) in Schizophrenia: a systematic review and meta-analysis by Omran Davarinejad, Saeid Komasi, Mohammad-Taher Moradi, Farzaneh Golmohammadi, Maryam Bahrami, Hamed Esmaeil Lashgarian, Masumeh Jalalvand, Sara Hookari, Fatemeh Kazemisafa

“…Subgroup analyses and meta-regression were performed, addressing heterogeneity and publication bias. Results Random-effects estimates (d = –0.80, p < 0.001) of the present meta-analysis revealed a significant mean difference in GDNF levels between SCZ patients and healthy controls. …”
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Association of preoperative body mass index with postoperative complications and survival for patients with gastric cancer: A systematic review and meta-analysis. by Zhenzhen Li, Lili Cui, Jing Sun, Wanlu Liu

“…Meta-analysis was performed using a random-effects model. Additionally, exploratory sensitivity and subgroup analyses were performed.…”
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Attendance of Patients with ophthalmological problems about Eye Protection from UV/blue Light Radiation from Sun light and Electronic Devices in Sulaimani City by Salah Qadir Mahmood, Muhammad Babakir-Mina, Salar Ibrahim Ali, Abdulrahman M. Ibrahem, Bakhtyar Kamal Talabany

“…A special designed cross-sectional questionnaire was performed on a random sampling for data collection from 9th September 2017 to 1st January 2018. …”
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Ecosystem carbon stock variation along forest stand ages: insight from eastern coast mangrove ecosystem of India by Muktipada Panda, Bikash R. Dash, Sudam C. Sahu

“…To achieve the results, twenty random plots were established (size: 20 m × 25 m) and suitable allometric equations along with species-specific wood density values were used to estimate the biomass and carbon stock. …”
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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study by Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao

“…Eight common machine learning methods (GDBT, AdaBoost, LGB, Logistic, Vote, XGB, Decision Tree, and Random Forest) and two common regressions (stepwise logistic regression and logistic regression with RCS) were implemented to predict the occurrence of GDM. …”
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The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review by Ricardo Smits Serena, Florian Hinterwimmer, Rainer Burgkart, Rudiger von Eisenhart-Rothe, Daniel Rueckert

“…Furthermore, our analysis reveals the current dominance of machine learning models in 76% on the surveyed studies, suggesting a preference for traditional models like linear regression, support vector machine, and random forest, but also indicating significant growth potential for deep learning models in this area. …”
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On-chip non-contact mechanical cell stimulation - quantification of SKOV-3 alignment to suspended microstructures by Sevgi Onal, Maan M. Alkaisi, Volker Nock

“…Although the accumulation of random genetic mutations has been traditionally viewed as the main cause of cancer progression, altered mechanobiological profiles of the cells and microenvironment also play a major role as a mutation-independent element. …”
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Association of geriatric nutritional risk index with renal prognosis and all-cause mortality among older patients with chronic kidney disease: a secondary analysis of CKD-ROUTE stu... by Lei Chen, Mengyao Yan, Jie Li, Xue Zhao, Lu Zeng, Zhumei Gao, Hongli Jiang, Limin Wei

“…Multivariable linear mixed regression models with random intercepts were used to assess the association between GNRI and estimated glomerular filtration rate (eGFR) decline per year.Results During the median follow-up period of 2.92 years, there were 123 (22.86%) CKD progression events, 44 (8.18%) deaths, and 76 (14.13%) cardiovascular events. …”
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Longitudinal analysis of academic stress and its effects on salivary cortisol, alpha-amylase, and academic outcomes: Study protocol. by Juan Luis Castillo-Navarrete, Alejandra Guzmán-Castillo, Claudio Bustos

“…(ii) Bivariate and multivariate analyses will be conducted to compare groups. (iii) Random intercept cross-lagged models will be used to assess the direction and reciprocal effects between variables over time. …”
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Incidence Rate of Type 2 Diabetes Mellitus after Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of 170,139 Women by Zhuyu Li, Yunjiu Cheng, Dongyu Wang, Haitian Chen, Hanqing Chen, Wai-kit Ming, Zilian Wang

“…Data from selected studies were extracted, and meta-analysis was performed using the random-effects model. Subgroups analyses were based on the sample size of gestational diabetes, geographic region, maternal age, body-mass index, diagnostic criteria, and duration of follow-up. …”
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Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders by Muhammad Waleed Iqbal, Muhammad Shahab, Zakir ullah, Guojun Zheng, Irfan Anjum, Gamal A. Shazly, Atrsaw Asrat Mengistie, Xinxiao Sun, Qipeng Yuan

“…Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds. …”
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Non-Invasive Cancer Detection Using Blood Test and Predictive Modeling Approach by Tarawneh AS, Al Omari AK, Al-khlifeh EM, Tarawneh FS, Alghamdi M, Alrowaily MA, Alkhazi IS, Hassanat AB

“…In addition, we experimented with the dataset’s missing values using the histogram gradient boosting (HGB) model.Results: The feature ranking method demonstrated the ability to distinguish cancer patients from healthy individuals based on hematological features such as WBCs, red blood cell (RBC) counts, and platelet (PLT) counts, in addition to age and creatinine level. The random forest (RF) classifier, followed by linear discriminant analysis (LDA) and support vector machine (SVM), achieved the highest prediction accuracy (ranging from 0.69 to 0.72 depending on the scenario and method investigated), reliably distinguishing between malignant and benign conditions. …”
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To Develop Biomarkers for Diabetic Nephropathy Based on Genes Related to Fibrosis and Propionate Metabolism and Their Functional Validation by Sha Li, Jingshan Chen, Wenjing Zhou, Yonglan Liu, Di Zhang, Qian Yang, Yuerong Feng, Chunli Cha, Li Li, Guoyong He, Jun Li

“…Second, the intersection of DN-DEGs, PM-DEGs, and FRGs was taken to yield intersected genes. Random forest (RF) and recursive feature elimination (RFE) analyses of the intersected genes were performed to sift out biomarkers. …”
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Analyzing Gait Dynamics and Recovery Trajectory in Lower Extremity Fractures Using Linear Mixed Models and Gait Analysis Variables by Mostafa Rezapour, Rachel B. Seymour, Suman Medda, Stephen H. Sims, Madhav A. Karunakar, Nahir Habet, Metin Nafi Gurcan

“…We employed a linear mixed model (LMM) to analyze these variables over time, incorporating both fixed and random effects to account for individual differences and the time since injury. …”
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Antidiabetic agent use and clinical outcomes in patients with diabetes hospitalized for COVID-19: a systematic review and meta-analysis by Jordan N. Keels, Isabella R. McDonald, Christopher S. Lee, Andrew A. Dwyer, Andrew A. Dwyer

“…Aggregated data were synthesized by treatment regimen and reported descriptively. Random effects meta-analyses were performed to assess relative risk and prevalence of mortality.ResultsAfter removing duplicates, title and abstract screening of 4,898 articles identified 118 articles for full-text review and 35 articles were retained for analysis. …”
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Entrepreneurial experience and venture success: A comprehensive meta-analysis of performance determinants by Matúš Grežo, Róbert Hanák

“…We investigated the effect of five determinants of this relationship, namely the type of experience, type of performance, venture age, size of managerial team, and composition of managerial team. A random effect model was applied and the correlation coefficient was used as an indicator of effect size. …”
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Knockdown resistance (kdr)-associated organochlorine resistance in mosquito-borne diseases (Culex pipiens): A systematic review and meta-analysis by Ebrahim Abbasi, Salman Daliri, Asghar Talbalaghi, Fatemeh Mehrpouya, Maryam Hasanzadeh arab, Atena Aslvaeli, Mohammad Djaefar Moemenbellah-Fard

“…The statistical analysis of the data was performed using random and fixed effects model in the meta-analysis, Cochran's test, I2 index, and meta-regression by STATA software version 17. …”
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