Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…Furthermore, an optimal predictive model was developed for CKD using ten machine learning algorithms and enhanced model interpretability with the Shapley Additive Explanations (SHAP) method. …”
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Developing Financial Forecast Modeling With Deep Learning On Silver/Ons Parity by Adem Üntez, Mümtaz İpek

“…However, as a feature of the LSTM algorithm, it clearly predicted the daily closing values, and did not specify an estimation as a range and direction as in the study with the ARIMA architec-ture. …”
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The relationship between the CYP2C19*17 genetic polymorphism and the efficacy and safety of diazepam in patients with alcohol withdrawal syndrome by V. Yu. Skryabin, M. S. Zastrozhin, E. A. Grishina, K. A. Ryzhikova, V. V. Shipitsyn, I. V. Barna, T. E. Galaktionova, A. S. Sorokin, E. A. Bryun, D. A. Sychev

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Enhancing wheat yellow rust detection through modified deep learning approach by Shant Kumar, Rohit Singh, Sudheer Kumar, Sandeep Gupta

“…A newly established dataset named Yellow Rust 2022–2023 (YR-22/23) is used to estimate and compare the performance of considered ML/DL algorithms. Additionally, a benchmarked dataset named YellowRust-19 is considered for cross validation of ML/DL algorithms. …”
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Adherence to Clinical Quidelines on Preoperative Assessment and Correction of Cardiovascular Risk in Non-cardiac Surgery by M. D. Nigmatkulova, E. B. Kleymenova, L. P. Yashina, V. A. Otdelenov, S. A. Payushchik, O. D. Konova, D. A. Sychev

“…The number of inappropriate ECGs and echocardiographies, as well as incorrect treatment with beta-blockers, HMG CoA reductase inhibitors and ACE inhibitors (ARBs) in perioperative period evidence that the adherence of physicians to the clinical guidelines on preoperative assessment and perioperative management of patients remains low.It is reasonably to develop risk-based interdisciplinary protocols for preoperative examination, algorithms for interdisciplinary communication and interaction between specialists and the healthcare levels, as well as physicians' education for better adherence to clinical guidelines.…”
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Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study by Hamid Reza Marateb, Mahsa Mansourian, Amirhossein Koochekian, Mehdi Shirzadi, Shadi Zamani, Marjan Mansourian, Miquel Angel Mañanas, Roya Kelishadi

“…We applied the XGBoost algorithm to analyze key noninvasive variables, including self-rated health, sunlight exposure, screen time, consanguinity, healthy and unhealthy dietary habits, discretionary salt and sugar consumption, birthweight, and birth order, father and mother education, oral hygiene behavior, and family history of dyslipidemia, obesity, hypertension, and diabetes using five-fold cross-validation. …”
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OPERATIONAL ANALYSIS OF COMPLEX MEDICAL STATES BY PHOTONICS METHODS by A. I. Larkin, K. A. Trukhanov

“…Inverse two-phase coding and operational analysis of multi-parameter data can realize a number of probabilistic algorithms. The possibility and expediency of realization of not only the correlation algorithm underlying the holographic image recognition but also universal statistical algorithms using photonics methods is substantiated. …”
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Harmonizing Landsat-8 OLI and Sentinel-2 MSI: an assessment of surface reflectance and vegetation index consistency by Jiaqi Zhang, Xiaocheng Zhou, Xueping Liu, Xiaoqin Wang, Guojin He, Youshui Zhang

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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

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Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

“…Results and conclusion: The potential of AI algorithms is also being extended for predicting the onset of diseases in the future and for predicting the long-term prognosis of diseases. …”
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Deep Learning-Based Postural Asymmetry Detection Through Pressure Mat by Iker Azurmendi, Manuel Gonzalez, Gustavo García, Ekaitz Zulueta, Elena Martín

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DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network by Chunyu Dong, Jing Liu, Shenglong Xie

“…In the intelligent transformation of education, accurate recognition of students’ classroom behavior has become one of the key technologies for enhancing the quality of instruction and the efficacy of learning. …”
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Using Age- and Size-Corrected Measures of Technical Skill to Better Assess the Performances of Youth Soccer Players by Thiago V. Camata, Andrew H. Hunter, Nicholas M. A. Smith, Mathew S. Crowther, Paulo R. P. Santiago, Robbie S. Wilson

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Internet of Things Assisted Plant Disease Detection and Crop Management Using Deep Learning for Sustainable Agriculture by Eman A. Al-Shahari, Ghadah Aldehim, Mohammed Aljebreen, Jehad Saad Alqurni, Ahmed S. Salama, Sitelbanat Abdelbagi

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Overview of Tensor-Based Cooperative MIMO Communication Systems—Part 2: Semi-Blind Receivers by Gérard Favier, Danilo Sousa Rocha

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K-Nearest Neighbors hybrid method for maximum power point tracking under partial shading for photovoltaic power systems by Djamel Guessoum, Maen Takrouri, Mohammad Rabih, Maissa Farhat, Sufian A. Badawi

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Advanced Color Edge Detection Using Clifford Algebra in Satellite Images by Uzair Aslam Bhatti, Zhou Ming-Quan, Qingsong Huo, Sajid Ali, Aamir Hussain, Yan Yuhuan, Zhaoyuan Yu, Linwang Yuan, Saqib Ali Nawaz

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A novel deep learning approach for investigating liquid fuel injection in combustion system by Syed Azeem Inam, Abdullah Ayub Khan, Noor Ahmed, Tehseen Mazhar, Tariq Shahzad, Sunawar Khan, Mamoon M. Saeed, Habib Hamam

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Novel machine learning paradigms-enabled methods for smart building operations in data-challenging contexts: Progress and perspectives by Fan Cheng, Lei Yutian, Mo Jinhan, Wang Huilong, Wu Qiuting, Cai Jiena

“…This review aims to present the progress and perspectives on the effective utilization of novel machine learning paradigms for three major building energy management tasks, i.e., building energy predictions, fault detection and diagnosis, and control optimizations. …”
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Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation by WANG Qingyuan, WEI Mi, HU Yunqing, WANG Jianhua, JIANG Fan, ZHANG Zhengfang, WANG Kaiyun

“…Therefore, this paper recommends considering dynamic effects not captured by existing mechanism models and exploring order reduction equivalency in future research. Secondly, the strong nonlinear coupling characteristics between cars in long-consist trains and the impact of air braking characteristics on longitudinal impulses during train operation, still pose significant challenges for optimizing the control of heavy-haul trains. …”
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