A New Method of Central Axis Extracting for Pore Network Modeling in Rock Engineering by Xiao Guo, Kairui Yang, Haowei Jia, Zhengwu Tao, Mo Xu, Baozhu Dong, Lei Liu

“…Firstly, digital core was reconstructed by using the Markov Chain Monte Carlo (MCMC) method based on the binary images of a rock cutting plane taken from heavy oil reservoir sandstone. …”
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Second-line systemic treatment for metastatic colorectal cancer: A systematic review and Bayesian network meta-analysis based on RCT. by Chengyu Sun, Enguo Fan, Luqiao Huang, Zhengguo Zhang

“…<h4>Methods</h4>We searched PubMed, Web of Science, EMBASE, and Cochrane Library for RCTs comparing second-line systemic treatments for mCRC from the inception of each database up to February 3, 2024. Markov Chain Monte Carlo (MCMC) technique was used in this network meta-analysis (NMA) to generate the direct and indirect comparison results among multiple treatments in progression-free survival (PFS), overall response rate (ORR), overall survival (OS), complete response (CR), partial response (PR), grade 3 and above adverse events (Grade ≥ 3AE), and any adverse events (Any AE). …”
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Comparison of Hydrus and iStent microinvasive glaucoma surgery implants in combination with phacoemulsification for treatment of open-angle glaucoma: systematic review and network... by Xiaoyu Wang, Rongrong Hu, Dongyu Guo, Nan Hong, Xiuyuan Xuan

“…The network meta-analysis was conducted within a Bayesian framework using the Markov Chain Monte Carlo method in ADDIS software.Results Six prospective RCTs comprising 1397 patients were identified. …”
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New probabilistic methods for quantitative climate reconstructions applied to palynological data from Lake Kinneret by T. Netzel, A. Miebach, T. Litt, A. Hense

“…To solve this model, we use Markov chain Monte Carlo (MCMC) sampling methods. During the inference process, our new method generates taxa weights and biome climate ranges. …”
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Clinical efficacy of 0.1% cyclosporine A in dry eye patients with inadequate responses to 0.05% cyclosporine A: a switching, prospective, open-label, multicenter study by Sook Hyun Yoon, Eun Chul Kim, In-Cheon You, Chul Young Choi, Jae Yong Kim, Jong Suk Song, Joon Young Hyon, Hong Kyun Kim, Kyoung Yul Seo

“…Statistical analysis was performed on the full analysis set (FAS) using the Markov Chain Monte Carlo (MCMC) method to account for missing data. …”
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A novel model-based meta-analysis to indirectly estimate the comparative efficacy of two medications: an example using DPP-4 inhibitors, sitagliptin and linagliptin, in treatment o... by Yan Gong, James Rogers, Christian Friedrich, Sanjay Patel, Alexander Staab, Jorge Luiz Gross, Daniel Polhamus, William Gillespie, Brigitta Ursula Monz, Silke Retlich

“…Comparison of two oral dipeptidyl peptidase (DPP)-4 inhibitors, sitagliptin and linagliptin, for type 2 diabetes mellitus (T2DM) treatment was used as an example.Design Systematic review with MBMA.Data sources MEDLINE, EMBASE, http://www.ClinicalTrials.gov, Cochrane review of DPP-4 inhibitors for T2DM, sitagliptin trials on Food and Drug Administration website to December 2011 and linagliptin data from the manufacturer.Eligibility criteria for selecting studies Double-blind, randomised controlled clinical trials, ≥12 weeks’ duration, that analysed sitagliptin or linagliptin efficacies as changes in glycated haemoglobin (HbA1c) levels, in adults with T2DM and HbA1c &gt;7%, irrespective of background medication.Model development and application A Bayesian model was fitted (Markov Chain Monte Carlo method). The final model described HbA1c levels as function of time, dose, baseline HbA1c, washout status/duration and ethnicity. …”
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Cancer phylogenetic tree inference at scale from 1000s of single cell genomes by Salehi, Sohrab, Dorri, Fatemeh, Chern, Kevin, Kabeer, Farhia, Rusk, Nicole, Funnell, Tyler, Williams, Marc J., Lai, Daniel, Andronescu, Mirela, Campbell, Kieran R., McPherson, Andrew, Aparicio, Samuel, Roth, Andrew, Shah, Sohrab P., Bouchard-Côté, Alexandre

“…The sitka transformation allows us to design novel scalable Markov chain Monte Carlo (MCMC) algorithms. Moreover, we introduce a novel point mutation calling method that incorporates the CN data and the underlying phylogenetic tree to overcome the low per-cell coverage of scWGS. …”
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PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy by Lovro Palaversa, Željko Ivezić, Neven Caplar, Karlo Mrakovčić, Bob Abel, Oleksandra Razim, Filip Matković, Connor Yablonski, Toni Šarić, Tomislav Jurkić, Sandro Campos, Melissa DeLucchi, Derek Jones, Konstantin Malanchev, Alex I. Malz, Sean McGuire, Mario Jurić

“…The computation speed is about 10 ms per star on a single core for both optimized grid search and Markov Chain Monte Carlo methods; we show in a companion paper by K. …”
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