Modern algorithms for statin therapy by V. A. Susekov

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Non-Destructive Methods Based on Machine Learning for the Prediction of Sweet Potato Leaf Area: A Comparative Approach by Joao Everthon Da Silva Ribeiro, Ester Dos Santos Coelho, Antonio Gideilson Correia Da Silva, Pablo Henrique De Almeida Oliveira, Elania Freire Da Silva, Gisele Lopes Dos Santos, Anna Kezia Soares De Oliveira, John Victor Lucas Lima, Walter Esfrain Pereira, Lindomar Maria Da Silveira, Aurelio Paes Barros

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Algorithm of echocardiography in pregnant women by S. G. Gorokhova, T. E. Morozova, A. A. Arakelyants, E. A. Barabanova, E. G. Dyakonova

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Enhancing Upper Limb Exoskeletons Using Sensor-Based Deep Learning Torque Prediction and PID Control by Farshad Shakeriaski, Masoud Mohammadian

Subjects: “…torque estimation and prediction…”
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A cluster randomized trial of a Multicomponent Clinical Care Pathway (MCCP) to improve MASLD diagnosis and management in primary care: study protocol by Kyler M. Godwin, Larissa Grigoryan, Aaron P. Thrift, Hao Duong, Fasiha Kanwal, Traber Giardina, Himabindu Kadiyala, Andrew Zimolzak, Kavish R. Patidar, Hashem B. El-Serag

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A multifaceted comparative analysis of incremental dynamic and static pushover methods in bridge structural assessment, integrated with artificial neural network and genetic algori... by Ashwini Satyanarayana, V. Sindura, L. Geetha, Rakesh Kumar, Mohd Asif Shah, Mary Subaja Christo

“…The results of static pushover analysis and incremental dynamic analysis (IDA) are predicted and compared in this work using ANN and GA, which offers a deeper understanding of their predictive capabilities.…”
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Integrating user demographic parameters for mouse behavioral biometric-based assessment fraud detection in online education platforms by Aditya Subash, Insu Song, Ickjai Lee, Kyungmi Lee

Subjects: “…Cross-referencing fusion algorithm…”
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Dance Movement Interference Suppression Algorithm Based upon Contour Model and AdaBoost Algorithm by Jiaxi Xu

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Prediction of R1234yf flow boiling behavior in horizontal, vertical, and inclined tubes using machine learning techniques by Farzaneh Abolhasani, Behrang Sajadi, Mohammad Ali Akhavan-Behabadi

“…In the present study, the utilization of machine learning algorithms (MLAs) is proposed for the prediction of the heat transfer coefficient and pressure drop in horizontal, vertical, and inclined tubes during flow boiling of R1234yf. …”
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Proactive spectrum handoff in distributed cognitive radio networks by Hua JIANG, Li-chuan MA, Ding-yu YAN, Nan PAN

Subjects: “…distributed cognitive radio network;spectrum handoff;spectrum prediction;task allocation algorithm of ant colony…”
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Novel load balancing mechanism for cloud networks using dilated and attention-based federated learning with Coati Optimization by Atul B. Kathole, Viomesh Kumar Singh, Ankur Goyal, Shiv Kant, Amit Sadanand Savyanavar, Swapnaja Amol Ubale, Prince Jain, Mohammad Tariqul Islam

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Predicting postpartum female sexual interest/arousal disorder via adiponectin and biopsychosocial factors: a cohort-based decision tree study by Saiedeh Sadat Hajimirzaie, Najmeh Tehranian, Amin Golabpour, Ahmad Khosravi, Seyed Abbas Mousavi, Afsaneh Keramat, Mehdi Mirzaii

“…The C4.5 decision tree algorithm effectively analyzes multiple variables to identify key relationships. …”
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Enhancing PM_2.5 Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms by Iman Zandi, Ali Jafari, Aynaz Lotfata

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Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory. by Qi Dai, Xiao-Yan Liu, Fang-Yi Sun, Fang-Rong Ren

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Modelling and Predicting the Breaking Strength and Mass Irregularity of Cotton Rotor-Spun Yarns Containing Cotton Fiber Recovered from Ginning Process by Using Artificial Neural Network Algorithm by Mohsen Shanbeh, Hossein Hasani, Somayeh Akhavan Tabatabaei

“…The purpose of this study was to develop predictive models of breaking strength and mass irregularity (CV𝑚%) of cotton waste rotor-spun yarns containing cotton waste collected from ginning process by using the artificial neural network trained with backpropagation algorithm. …”
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A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort study by Xingjian Xiao, Xiaohan Yi, Zumin Shi, Zongyuan Ge, Hualing Song, Hailei Zhao, Tiantian Liang, Xinming Yang, Suxian Liu, Bo Sun, Xianglong Xu

“…We employed nine machine learning algorithms to construct predictive models for gastric ulcers over the next seven years (2011–2018, with 1482 samples) and the next three years (2014–2018, with 2659 samples). …”
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Accuracy of cross-sectional imaging in predicting tumor viability using the LI-RADS treatment response algorithm after image-guided percutaneous ablation with radiologic-pathologic explant correlation by Anuradha S. Shenoy-Bhangle, M. Saad Malik, Aamir Ali, Nan Nancy Jiang, Syed Yasir Andrabi, Amit Singal, Michael P. Curry, Maria-Andreea Catana, Devin E. Eckhoff, Salomao Faintuch, Muneeb Ahmed, Imad Ahmad Nasser, Ammar Sarwar

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Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and meta-analysis by Jimmy Londono, Shohreh Ghasemi, Altaf Hussain Shah, Amir Fahimipour, Niloofar Ghadimi, Sara Hashemi, Zohaib Khurshid, Mahmood Dashti

“…This meta-analysis included 21 of 577 articles initially collected on the accuracy of ML algorithms for detecting and predicting anatomical landmarks. …”
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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Method by Yunzhe Guo, Qidan Zhu, Jinyou Mou

Subjects: “…non-dominated sorting genetic algorithm II…”
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Development of an algorithm to improve on the National Early Warning Score 2 (NEWS2) system's accuracy in predicting critical outcomes using additional patient data and amendments to the scoring process by Lynsey Threlfall, Chris Plummer, Edward Meinert, Cen Cong, Madison Milne-Ives

“…Using these datasets, we will train and test an algorithm that optimises the variables and their weightings to predict the risk of key clinical outcomes, including mortality, intensive care unit admission, sepsis and cardiac arrest, to demonstrate a proof of concept for a modified scoring system. …”
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