Challenges in the diagnosis of heart failure with preserved ejection fraction in individuals with obesity by Bas M. van Dalen, Jie Fen Chin, Praveen A. Motiram, Anneke Hendrix, Mireille E. Emans, Jasper J. Brugts, B. Daan Westenbrink, Rudolf A. de Boer

“…In this review, we examine these diagnostic challenges and propose a diagnostic algorithm specifically tailored to improve the accuracy and reliability of HFpEF diagnosis in this growing patient demographic. …”
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The TB27 Transcriptomic Model for Predicting Mycobacterium tuberculosis Culture Conversion by Maja Reimann, Korkut Avsar, Andrew DiNardo, Torsten Goldmann, Gunar Günther, Michael Hoelscher, Elmira Ibraim, Barbara Kalsdorf, Stefan Kaufmann, Niklas Köhler, Anna Mandalakas, Florian Maurer, Marius Müller, Dörte Nitschkowski, Ioana Olaru, Cristina Popa, Andrea Rachow, Thierry Rolling, Helmut Salzer, Patricia Sanchez-Carballo, Maren Schuhmann, Dagmar Schaub, Victor Spinu, Elena Terhalle, Markus Unnewehr, Nika Zielinski, Jan Heyckendorf, Christoph Lange

“…Methods: Using a multi-step machine learning algorithm to identify an RNA-based algorithm to predict the remaining time to culture conversion at flexible time points during anti-tuberculosis therapy.  …”
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Spatial Characteristics and Influence of Topography and Synoptic Systems on PM2.5 in the Eastern Monsoon Region of China by Shengli Zhu, Zhaowen Wang, Kai Qu, Jun Xu, Ji Zhang, Haiyi Yang, Wenxin Wang, Xiao Sui, Min Wei, Houfeng Liu

“…According to synoptic systems, regional PM2.5 pollution episodes were classified into three categories, including Uniform Pressure field (UP, 60.00%), Pre-High Pressure (PreHP, 30.91%) and Inverted-Trough (IT, 9.09%). The K-Means algorithm combined with the HYSPLIT backward trajectory clustering analysis indicated four clusters under UP controlled, and under weak pressure field was responsible for the elevation of PM2.5 concentration, where the Beijing-Tianjin-Hebei and its surrounding areas were the most polluted region. …”
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Back-Calculation of Soil Modulus from PFWD Based on a Viscoelastic Model by Rui Zhang, Tianzeng Ren, Md Ashrafuzzaman Khan, Yusheng Teng, Jianlong Zheng

“…A quasi-static dynamic analysis technique of Laplace transformation and a modified Gauss–Newton optimization algorithm were adopted in the proposed method. The back-calculation program was compiled with MATLAB. …”
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Intelligent Time-Domain Parameters Matching for Shock Response Spectrum and Its Experimental Validation in Active Vibration Control Systems by Jinxin Liu, Liangdong Yang, Xingwu Zhang, Ruqiang Yan, Xuefeng Chen

“…A variable-weight method has been introduced to combine the effects of hundreds objective functions so that the optimization problem can be solved by using the genetic algorithm. The frequency response function of the shaking system has been taken into consideration in the calculation of the objective function, so the synthesized TSW can be applied directly to the SRS test. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
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Formulation and validation of mathematical model for co-sputtering conditions to attain stoichiometric CZTS films: Expedience of using all metal sulfide targets by Munira Sultana, Afrina Sharmin, Md Rashed Alam, Shahran Ahmed, Md Aftab Ali Shaikh, M.S. Bashar

“…Following that, the films are annealed at 470 °C without sulfur (S). An algorithm based on the deposition rate of the previously specified targets set the co-sputtering condition, which maintains a deposition pressure of 5, 10, 15, and 20 mTorr. …”
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Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer by Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang

“…Subsequently, for each frequency band of the load sequence, the LightGBM algorithm quantifies the correlation between the load and various influencing factors. …”
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Risk factors of development of hepatocellular carcinoma by V. T. Ivashkin, M. A. Morozova, M. V. Mayevskaya, I. A. Sokolina, Ye. N. German, M. V. Bundina

“…To draw attention of general practitioners to the risk factors of hepatocellular carcinoma (HCC) development, to define group of patients with high probability of development of this tumor, to outline algorithm of screening diagnostics for patients of high risk group.Original positions of the report. …”
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Applying Machine Learning Techniques to Identify Undiagnosed Patients with Exocrine Pancreatic Insufficiency by Bruce Pyenson, Maggie Alston, Jeffrey Gomberg, Feng Han, Nikhil Khandelwal, Motoharu Dei, Monica Son, Jaime Vora

“…**Methods:** A machine learning algorithm was developed in Scikit-learn, a Python module. …”
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Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach by João C. O. Marra, Eduardo M. O. Lopes, José João de Espíndola, Walter Antônio Gontijo

“…Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber), the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm) working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. …”
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Fuzzy Comprehensive Evaluation Model of Project Investment Risk Based on Computer Vision Technology by Hongjian Wang

“…In addition, this paper also trains and tests the risk evaluation model of this research through the support vector machine classification algorithm, the real-time embedded system, and the average random consistency index. …”
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Gluteus medius muscle activation patterns during gait with Cerebral Palsy (CP): A hierarchical clustering analysis. by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Katharina S Gather, Sebastian I Wolf

“…A hybrid K-means-PSO clustering algorithm was employed, followed by hierarchical clustering. …”
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Frontier machine learning techniques for melanoma skin cancer identification and categorization: An in-Depth review by Viomesh Singh, Kavita A. Sultanpure, Harshwardhan Patil

“…In the review we Openly discussed the inherent limitations and quirks of each algorithm, affording them the spotlight they deserve.…”
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Cholestasis in Chronic Liver Disease and the Role of Ademetionine in its Treatment (Literature Review and Expert Panel Resolution) by K. L. Raikhelson, A. O. Bueverov, E. A. Kondrashina, M. V. Maevskaya, I. B. Khlynov, E. N. Shirokova, V. T. Ivashkin

“…The relevance of the existing algorithm for diagnosing cholestasis in real clinical practice was assessed. …”
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Optimization of Multiple Tuned Mass Dampers for Road Bridges Taking into Account Bridge-Vehicle Interaction, Random Pavement Roughness, and Uncertainties by Letícia Fleck Fadel Miguel, Guilherme Piva dos Santos

“…The proposed optimization problem is solved by employing the Whale Optimization Algorithm (WOA). The results showed the excellent ability of the proposed methodology, reducing the bridge’s DAF to acceptable values for all analyzed cases, considering or not the uncertainties present in the system. …”
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Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement. by José L Safanelli, Tomislav Hengl, Leandro L Parente, Robert Minarik, Dellena E Bloom, Katherine Todd-Brown, Asa Gholizadeh, Wanderson de Sousa Mendes, Jonathan Sanderman

“…From independent model evaluation, we found that Cubist comes out as the best-performing ML algorithm for the calibration and delivery of reliable outputs (prediction uncertainty and representation flag). …”
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Digital fundus image quality assessment by V. V. Starovoitov, Y. I. Golub, M. M. Lukashevich

“…For this, a new universal retinal image binarization algorithm is proposed. By analyzing result of the binarization, it is possible to identify and remove imagesoutliers, which show not the retina, but other objects. …”
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Cross-Spectral Cross-Distance Face Recognition via CNN with Image Augmentation Techniques by Nisa Adilla Rahmatika, Fitri Arnia, Maulisa Oktiana

“…The Multi-task Cascaded Convolutional Networks (MTCNN) algorithm was employed for face detection, followed by image preprocessing steps including resizing to 224x224 pixels, normalization, and homomorphic filtering. …”
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Research on Inertial Isolation Rotation Modulation of Dual-Axis Inertial Navigation Based on Multi-Error Coupling Characteristics by Bo Zhang, Changhua Hu, Silin Hou, Jianxun Zhang, Jianfei Zheng, Xuan Liu

“…A dual-axis inertial isolation shaft system installation error compensation algorithm was designed, and an improvement was made based on the traditional sixteen-sequence rotation scheme to compensate for the projection components of the Earth’s rotation and carrier motion on the inner and outer frame rotation axes, achieving the inertial isolation rotation modulation function of dual-axis inertial navigation. …”
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