Applicability of Machine Learning and Mathematical Equations to the Prediction of Total Organic Carbon in Cambrian Shale, Sichuan Basin, China by Majia Zheng, Meng Zhao, Ya Wu, Kangjun Chen, Jiwei Zheng, Xianglu Tang, Dadong Liu

“…This study introduces three key innovations to address these challenges: (1) A Dynamic Weighting–Calibrated Random Forest Regression (DW-RFR) model integrating high-resolution Gamma-Ray-guided dynamic time warping (±0.06 m depth alignment precision derived from 237 core-log calibration points using cross-validation), Principal Component Analysis-Deyang–Anyue Rift Trough Shapley Additive Explanations (PCA-SHAP) hybrid feature engineering (89.3% cumulative variance, VIF < 4), and Bayesian-optimized ensemble learning; (2) systematic benchmarking against conventional ΔlogR (R² = 0.700, RMSE = 0.264) and multi-attribute joint inversion (R² = 0.734, RMSE = 0.213) methods, demonstrating superior accuracy (R² = 0.917, RMSE = 0.171); (3) identification of Gamma Ray (r = 0.82) and bulk density (r = −0.76) as principal TOC predictors, contrasted with resistivity’s thermal maturity-dependent signal attenuation (r = 0.32 at Ro > 3.0%). …”
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What proportion of people have long-term pain after total hip or knee replacement? An update of a systematic review and meta-analysis by Rachael Gooberman-Hill, Michael R Whitehouse, Hung-Yuan Cheng, Andrew David Beswick, Vikki Wylde, Wendy Bertram, Mohammad Ammar Siddiqui

“…The risk of bias assessment was performed using Hoy’s checklist. Bayesian, random-effects meta-analysis was used to synthesise the results.Results For TKR, 68 studies with 89 time points, including 598 498 patients, were included. …”
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Comparative efficacy of acupuncture for chronic low back pain: A network meta-analysis by Feng Gao, Dongming Jia, Shengxia Xue

“…LP + EA also significantly improved functional capacity, with a mean difference of −11.7 points (95 % CrI: −15.3 to −8.1) on the Oswestry Disability Index (ODI), approaching the MCID of 10 points. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

“…The construction industry increasingly embraces machine learning (ML) to estimate concrete properties and optimize cost and time accurately. This study employs independent ML methods, gene expression programming (GEP), multi-expression programming (MEP), XGBoost, and Bayesian estimation model (BES) to predict SFRC compressive strength (CS) at high temperatures. 307 experimental data points from published studies were utilized to develop the models. …”
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Association between trajectory of triglyceride-glucose index and all-cause mortality in critically ill patients with atrial fibrillation: a retrospective cohort study by Shangsong Shi, Feng Xue, Tingbo Jiang, Lin Ling

“…We applied group-based trajectory modeling to identify distinct TyG index trajectories, selecting the optimal model based on the Bayesian information criterion (BIC), Akaike information criterion (AIC), average posterior probability (AvePP), and clinical interpretability. …”
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Early detection to improve outcome in people with undiagnosed psoriatic arthritis: the PROMPT research programme including RCT by Neil McHugh, Laura Bojke, Mel Brooke Turfrey, Rachel Charlton, Myka Ransom, Laura C Coates, Howard Collier, Claire Davies, Emma Dures, Philip Helliwell, Jana James, Anya Lissina, Vishnu B Madhok, Alison L Nightingale, Jonathan Packham, Catherine Smith, Eldon Spackman, Cerys Tassinari, William Tillett, Sarah T Brown

“…EPIdemiology of psoriatiC arthritis study: Bayesian networks identified clusters of symptoms that can accurately predict the development of psoriatic arthritis (area under the curve 0.73, 95% CI 0.70 to 0.75). …”
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