Comparing the effectiveness, safety and tolerability of interventions for depressive symptoms in people with multiple sclerosis: a systematic review and network meta-analysis proto... by Amalia Karahalios, Allan G Kermode, Yvonne C Learmonth, Julia Lyons, Stephanie Campese, Alexandra Metse, Claudia H Marck

“…If possible, we will synthesise the evidence by fitting a frequentist network meta-analysis model with multivariate random effects, or a pairwise random-effects meta-analysis model. …”
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Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers by Hengyan Zhang, Ye Zhou, Heguo Yan, Changxing Huang, Licong Yang, Yangwen Liu

“…Feature selection methods such as LASSO, SVM-RFE and random forest algorithm were applied to localize possible therapeutic target genes. …”
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Machine learning-based estimation of crude oil-nitrogen interfacial tension by Safia Obaidur Rab, Subhash Chandra, Abhinav Kumar, Pinank Patel, Mohammed Al-Farouni, Soumya V. Menon, Bandar R. Alsehli, Mamata Chahar, Manmeet Singh, Mahmood Kiani

“…The evaluation study proved that Random Forest is the most accurate developed intelligent model as it was characterized with acceptable R-squared (0.959), mean square error (1.65), average absolute relative error (6.85%) of unseen test datapoints as well as with correct trend prediction of IFT with regard to all input parameters of pressure, temperature and crude oil API. …”
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Prevalence of prolonged transitional neonatal hypoglycemia and associated factors in Ethiopia: A systematic review and meta-analysis. by Solomon Demis Kebede, Amare Kassaw, Tigabu Munye Aytenew, Kindu Agmas, Demewoz Kefale

“…<h4>Methods</h4>A weighted inverse-variance random-effects model was employed for the analysis. …”
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Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria by Zinabu Bekele Tadese, Teshome Demis Nimani, Kusse Urmale Mare, Fetlework Gubena, Ismail Garba Wali, Jamilu Sani

“…Six machine learning algorithms, namely, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Decision Tree, Random Forest, and eXtreme Gradient Boosting, were employed on a total sample size of 37,581 in Python 3.9 version. …”
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Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data by W. Li, S. B. M. Veldhuijsen, S. Lhermitte, S. Lhermitte

“…In the estimation process, 10 years of SSMIS observations (brightness temperature) and ASCAT observations (backscatter intensity) is used as input features to a random forest (RF) regressor. The regressor is first trained on time series of modelled density and satellite observations at randomly sampled pixels and then applied to estimate densities in dry-firn areas across Antarctica. …”
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Predictive model of acute kidney injury in critically ill patients with acute pancreatitis: a machine learning approach using the MIMIC-IV database by Shengwei Lin, Wenbin Lu, Ting Wang, Ying Wang, Xueqian Leng, Lidan Chi, Peipei Jin, Jinjun Bian

“…We performed feature selection using the random forest method. Model construction involved an ensemble of ML, including random forest (RF), support vector machine (SVM), k-nearest neighbors (KNN), naive Bayes (NB), neural network (NNET), generalized linear model (GLM), and gradient boosting machine (GBM). …”
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A Mechanistic, Stochastic Model Helps Understand Multiple Sclerosis Course and Pathogenesis by Isabella Bordi, Renato Umeton, Vito A. G. Ricigliano, Viviana Annibali, Rosella Mechelli, Giovanni Ristori, Francesca Grassi, Marco Salvetti, Alfonso Sutera

“…We show that relapses and remissions follow exponential decaying distributions, excluding periodic recurrences and confirming that relapses manifest randomly in time. It is found that a mechanistic model with a random forcing describes in a satisfactory manner the occurrence of relapses and remissions, and the differences in the length of time spent in each one of the two states. …”
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Simulation of slope soil erosion intensity with different vegetation patterns based on cellular automata model by Yan Sheng, Shangxuan Zhang, Long Li, Long Li, Zhiming Cao, Yu Zhang

“…This study focuses on the slopes of three planting patterns (uniform distribution, aggregation distribution, and random distribution), along with bare slopes, in the Baojiagou watershed of the Pisha Sandstone area, based on soil erosion intensity grade maps after rainfall from 2021 to 2023.MethodsA method combining Multi-Criteria Evaluation (MCE) and the CA-Markov model is used to analyze the spatial variation of soil erosion intensity types on different slopes. …”
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Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

“…After rigorous analysis, Random Forest emerged as the best-performing algorithm, exhibiting remarkable accuracy (87%), precision (78%), recall (95%), and f1-score (86%). …”
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Optimizing FPGA Resource Allocation for SHA-3 Using DSP48 and Pipelining Techniques by Agfianto Eko Putra, Oskar Natan, Jazi Eko Istiyanto

“…This method makes use of FPGA resources like Look-Up Tables (LUT), Look-Up Table Random Access Memory (LUTRAM), Flip-Flops (FF), Block RAM (BRAM), Digital Signal Processing (DSP), Input/Output (IO), and Buffer (BUFG). …”
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Gender characteristics, social determinants, and seasonal patterns of malaria incidence, relapse, and mortality in Sistan and Baluchistan province and other province of Iran: A sys... by Maryam Khazaee-Pool, Mahmood Moosazadeh, Mehran Asadi-Aliabadi, Fereshteh Yazdani, Koen Ponnet

“…The incidence rate of malaria relapse varied from 0.30% to 46%. Based on the random effect model, the malaria relapse rate in Iran was estimated at 9%. …”
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Exploring the feasibility of GF1-WFV data in estimating SPAD using spatiotemporal fusion algorithms by Annan Zeng, Jianli Ding, Jinjie Wang, Lijing Han, Haiyan Han, Shuang Zhao, Xiangyu Ge

“…In this study, we evaluated the performance of four fusion algorithms fusing Gaofen-1 WFV and MODIS data while also exploring their fusion accuracy. A random forest regression model was developed using the fused images and measured SPAD (Soil and Plant Analyzer Development) values, enabling large-scale, accurate, and dynamic monitoring of vegetation chlorophyll content. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. …”
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Systematic Review and Meta-Analysis on Human African Trypanocide Resistance by Keneth Iceland, Kasozi, Ewan Thomas, MacLeod, Susan Christina, Welburn

“…Data were analyzed using RevMan and random effect sizes were computed for the statistics at the 95% confidence interval. …”
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Provably secure and efficient proxy signature scheme by Jie ZENG, Wei NIE

“…Aiming at the situation above, a new efficient proxy signature scheme is proposed. The random oracles are combined in the scheme and a smaller vector norm blind message is used to control the dimension of proxy signature secret key. …”
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Cloud-based map alignment strategies for multi-robot FastSLAM 2.0 by Shimaa S Ali, Abdallah Hammad, Adly S Tag Eldien

“…Furthermore, this work improves the map alignment part using hybrid combination strategies, random sample consensus, and inter-robot observations to exploit fully their advantages. …”
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Host security threat analysis approach for network dynamic defense by Lixun LI, Bin ZHANG, Shuqin DONG

“…Calculating the host security threat in network dynamic defense (NDD) situation has to consider the vulnerabilities’ uncertainty because of dynamic mutation.Firstly,the vulnerabilities’ uncertainty caused by the mutation space and the mutation period was calculated by random sampling model,and combined with the CVSS,the attack success probability formula of single vulnerability was derived.Secondly,to avoid self-loop during the path searching process in multiple vulnerabilities situation,an improved recursive depth first algorithm which combined with node visited queue was proposed.Then,the host security threat was calculated based on attack success probability in the situation of multiple vulnerabilities and paths.Finally,approach’s availability and effectiveness were verified by an experiment conducted in a typical NDD situation.…”
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NUCLEOSOME ORGANIZATION IN PLANT DNA SATELLITES by V. N. Babenko, K. O. Kutashev, V. F. Matvienko

“…The curvature profiles in tandem repeats differ significantly from a random model. As many as 50 % of the monomers have a periodicity of DNA bends in the vicinity of 170 bp, fitting the wrapping length of a single nucleosome within two highest-order harmonics in the DNA curvature profile. …”
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Exploration and Analysis of Resource Scheduling and Management Mode in Future Space TT＆C Network by Hong ZHANG, Jia XUE, Bo REN, Xiaojun DU, Meng XUE

“…The running mode and existing issues of current resource scheduling system operation model of TT＆amp;C network were discussed firstly.Then the development trends of future resource scheduling and management models were summarized, included integration of data transmission, automation of system operation, intelligence of algorithm allocation, coexistence of random access and pre-allocation.In the end, accorded to the management demands of integration, automation and intelligentization, the operating framework of the future resource scheduling model was put forward.After that, the key technologies which need to be broken through of the framework were researched deeply.And the further construction object of resource scheduling research was proposed in order to provided a reference for subsequent engineering applications.…”
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