Oil Development Engineering Company, Tehran, Iran by Seyed Ali Mohammad Tajalli, Mazda Moattari, Vahid Naghavi, Mohammad Reza Salehizadeh

“…Leveraging a hybrid approach that combines the Extended Kalman Filter (EKF), Real-Time Transient Modeling (RTTM), and machine learning algorithms, the framework offers accurate insights into the pipeline’s operational status. …”
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Mapping forest types along ecological gradient in Pakistan by Naveed Ahmad, Syed Ghias Ali

“…Maxent modeling showed impressive predictive performance of all forest types (STPF, MTF and DTF) along ecological gradient with average AUC values of 0.968, 0.918, and 0.940 respectively and climatic variables have highest gain compared to topographic and soil predictors. …”
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MISHTI study evaluating hepatic fibrosis in type 2 diabetes patients in India by Debasis Datta, Krishna G. Seshadri, Samit Ghosal

“…Logistic regression models were used to identify independent predictors of significant fibrosis. The predictive performance of the models was evaluated using ROC curves. …”
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The Inversion of SPAD Value in Pear Tree Leaves by Integrating Unmanned Aerial Vehicle Spectral Information and Textural Features by Ning Yan, Yasen Qin, Haotian Wang, Qi Wang, Fangyu Hu, Yuwei Wu, Xuedong Zhang, Xu Li

“…The results showed the following: (1) both vegetation indices and textural features were significantly correlated with SPAD values, which were important indicators for estimating the SPAD values of pear leaves; (2) combining vegetation indices and textural features significantly improved the accuracy of SPAD value estimation compared with a single feature type; (3) the four machine learning algorithms demonstrated good predictive ability, and the OIA model outperformed the single model, with the model based on the OIA inversion model combining vegetation indices and textural features having the best accuracy, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> values of 0.931 and 0.877 for the training and validation sets, respectively. …”
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Model Development for Estimating Sub-Daily Urban Air Temperature Patterns in China Using Land Surface Temperature and Auxiliary Data from 2013 to 2023 by Yuchen Guo, János Unger, Tamás Gál

“…Our study offered a novel method for estimating sub-daily Tair patterns using open-source data and revealed the impacts of predictive variables on Tair estimation, which has important implications for urban thermal environment research.…”
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From support to recovery: the evolving role of LVAD in reversing heart failure by Bingqi Sun, Zhigang Liu

“…However, challenges persist, including the lack of predictive biomarkers, suboptimal GDMT adherence, and unresolved debates regarding concomitant cardiac procedures. …”
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A Review and Comparative Analysis of Solar Tracking Systems by Reza Sadeghi, Mattia Parenti, Samuele Memme, Marco Fossa, Stefano Morchio

“…Intelligent tracking systems, especially those leveraging machine learning and predictive analytics, demonstrate additional energy gains up to 7.83% under cloudy conditions compared to conventional algorithms. …”
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Problematic points of anticoagulant therapy for atrial fibrillation in certain Russian regions in 2016- 2019: results of a retrospective big data analysis by M. A. Druzhilov, O. Yu. Druzhilova, Z. A. Ilchenko, P. I. Chalaya, T. Yu. Kuznetsova

“…Anonymized data of patients with AF aged ³18 years (n=144431; men, 42,0%; mean age, 68,9±15,7 years; mean CHA2DS2-VASc score, 3,2±1,8) were extracted from the Webiomed predictive analytics service using continuous sampling from electronic health records in medical facilities of 6 Russian constituent entities (Republic of Bashkortostan, Republic of Buryatia, Republic of Karelia, Republic of Sakha (Yakutia), Perm Krai, Yamalo-Nenets Autonomous Okrug) for 2016-2019 using artificial intelligence technologies. …”
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The use of culturally adapted and translated depression screening questionnaires with South Asian haemodialysis patients in England. by Shivani Sharma, Sam Norton, Kamaldeep Bhui, Roisin Mooney, Emma Caton, Tarun Bansal, Clara Day, Andrew Davenport, Neill Duncan, Philip A Kalra, Maria Da Silva-Gane, Gurch Randhawa, Graham Warwick, David Wellsted, Magdi Yaqoob, Ken Farrington

“…Alternative screening cut-offs did not improve positive predictive values.<h4>Conclusions</h4>Culturally adapted translations of depression screening questionnaires are useful to explore symptom endorsement amongst South Asian patients. …”
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Statistics is not measurement: The inbuilt semantics of psychometric scales and language-based models obscures crucial epistemic differences by Jana Uher

“…It demonstrates that psychometrics cannot establish coordinated and calibrated modelling relations, thus generating only pragmatic quantifications with predictive power but precluding epistemically justified inferences on the phenomena studied. …”
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Hybrid Modeling of an Induction Machine to Support Bearing Diagnostics by Praneet Amitabh, Dimitar Bozalakov, Frederik De Belie

“…The ultimate goal of this methodology is to generate extensive datasets encompassing diverse operating conditions that can be used further to estimate the health of the bearing and possibly be used for training predictive algorithms to estimate bearing RUL in motors. …”
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Deterring Street Crimes Using Aerial Police: Data-Driven Joint Station Deployment and Patrol Path Planning for Policing UAVs by Zuyu Chen, Yan Liu, Shengze Hu, Xin Zhang, Yan Pan

“…In the first module, the street-level deterring effect of the UAVs is estimated using a prediction-enhanced method, which guides the UAVs to patrol the high-risk streets more efficiently. …”
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Integrated artificial intelligence approach for well-log fluid identification in dual-medium tight sandstone gas reservoirs by Wurong Wang, Wurong Wang, Linbo Qu, Linbo Qu, Dali Yue, Dali Yue, Wei Li, Wei Li, Junlong Liu, Wujun Jin, Jialin Fu, Jialin Fu, Jiarui Zhang, Jiarui Zhang, Dongxia Chen, Dongxia Chen, Qiaochu Wang, Qiaochu Wang, Sha Li, Sha Li

“…In summary, this novel and reliable method for log fluid prediction, significantly improved its accuracy and robustness compared with single models and traditional methods, providing a comprehensive perspective across geological and geophysical disciplines for fluid logging evaluation in dual-medium tight sandstone gas reservoirs.…”
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Machine learning and SHAP values explain the association between social determinants of health and post-stroke depression by Zhiwei Song, Jilin Weng, Yupeng Han, Wangyu Li, Yiya Xu, Yingchao He, Yinzhou Wang

“…Logistic regression was employed to analyse the association between SDoH and PSD, whereas Cox regression was utilized to assess the correlation between SDoH and all-cause mortality in PSD. The Boruta algorithm was employed for feature selection, and four machine learning models were constructed (CatBoost, Logistic, Multilayer Perceptron, and Random Forest) to evaluate the predictive effectiveness, calibration, and clinical applicability of these ML models. …”
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Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

“…Firstly，preprocess the collected raw load data and calculate the actual load value considering system energy loss； Secondly，the maximum information coefficient （MIC） is used to analyze the correlation between multiple loads and between multiple loads and weather factors，and to extract strongly correlated variables of multiple loads； Once again，the strongly correlated variables of multiple loads are substituted into CEEMDAN，and the load data is decomposed into stationary subsequences； Then，the feature sequence is substituted into the LSTM-MTL shared layer and the CSO algorithm is used to optimize the prediction model，achieving collaborative prediction of multiple loads； Finally，the performance of the constructed model was validated using a multivariate load dataset from a chemical park in Jilin City，Jilin Province，China. …”
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Evaluation of different in silico tools for the assessment of deleterious variants in acute myeloid leukemia by Wardah Qureshi, Muhammad Irfan, Ishtiaq Ahmad Khan, Muhammad Shakeel

“…Several algorithms have been developed and evaluated to predict deleterious variants. …”
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Hyperspectral Estimation of Tea Leaf Chlorophyll Content Based on Stacking Models by Jinfeng Guo, Dong Cui, Jinxing Guo, Umut Hasan, Fengqi Lv, Zixing Li

“…In this study, derivative transformations were first applied to preprocess the tea hyperspectral data, followed by the use of the Stable Competitive Adaptive Reweighted Sampling (SCARS) algorithm for feature variable selection. Finally, multiple individual machine learning models and stacking models were constructed to estimate tea LCC based on hyperspectral data, with a particular emphasis on analyzing how the selection of base models and meta-models affects the predictive performance of the stacking models. …”
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Unravelling Antimicrobial Resistance in <i>Mycoplasma hyopneumoniae</i>: Genetic Mechanisms and Future Directions by Raziallah Jafari Jozani, Mauida F. Hasoon Al Khallawi, Darren Trott, Kiro Petrovski, Wai Yee Low, Farhid Hemmatzadeh

“…Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. …”
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Height of Hydraulic Fracture Zone Based on PSO_LSSVM Model by Hebin Zhang, Tingting Wang, Bin Wu, Haijun Feng

“…At the same time, this study develops a particle swarm optimization algorithm based on adaptive inertia weight and a least squares support vector machine model to achieve height prediction of water conducting fracture zones. …”
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Identification of biomarkers for Laryngeal squamous cell carcinoma through Mendelian randomization and integrated bioinformatics analysis by Pengjian Zhang, Weizhang Chen, Kai Chen, Yuanhang Ye, Weijun Wu

“…The differences in immune landscapes between high-risk and low-risk groups were assessed using the CIBERSORT algorithm, and drug sensitivity was analyzed using the “oncoPredict” package. …”
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