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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Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat by Zhikai Cheng, Xiaobo Gu, Yadan Du, Zhihui Zhou, Wenlong Li, Xiaobo Zheng, Wenjing Cai, Tian Chang

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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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Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China by Gaohong Yin, Yanling Zhang, Yuxi Cao, Jongmin Park

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TECHNOLOGIES FOR DEVELOPING DECISION SUPPORT SYSTEMS FOR THE DIAGNOSIS OF BLOOD DISORDERS USING CONVOLUTIONAL NEURAL NETWORKS by U. V. Maslikova, A. A. Supilnikov

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Destination-Aware Time-Constrained Task Allocation in Mobile Crowdsensing for Orienteering Application by Xia Hua, Lei Han

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Ten-year cardiovascular risk estimation in type 2 diabetes in Europe using the novel SCORE2-Diabetes model by G. G. Arabidze, M. N. Mamedov, H. R. Akhundova

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Real-Time Parameter Control for Trajectory Generation Using Reinforcement Learning With Zero-Shot Sim-to-Real Transfer by Chang-Hun Ji, Gyeonghun Lim, Youn-Hee Han, Sungtae Moon

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Comparing the Effectiveness of R and S Roughness Parameters on Surfaces Lubricated with Standardized Nominal Particle Size Lubricants by Leire Mendieta-Echevarría, María Ana Sáenz-Nuño, Eva María Rubio

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Detection and Optimization of Traffic Networks Based on Voronoi Diagram by Rui Tao, Jian Liu, Yuqing Song, Rui Peng, Dali Zhang, Jiangang Qiao

“…Experiments illustrated that the proposed method outperforms the existing smoothing-based methods in sensitivity, positive predictivity, and accuracy.…”
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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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The Intelligent Recognition of Speech Emotions: Survey Study by Ali Abdulwahhab Yehya al_saffar, Fawziya Ramo

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Options for Strengthening the Ensemble of Hypotheses under Uncertainty of the Objective Learning Function Formation by A. F. Chernyavsky, A. I. Kazlova

“…Intelligent learning systems traditionally consist of three main components: a student model, which is a block with information about the student; a model of the learning process that sets the form for presenting information to the student and the type of quality assessment of the student’s activity; the model interface as a link between the expert block of the intelligent learning system and other learning algorithms in the components of educational systems. …”
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