Discovery of PRMT5 N‑Terminal TIM Barrel Ligands from Machine-Learning-Based Virtual Screening by Zhihang Shen, Gustavo Seabra, Jason Brant, Kalyanee Shirlekar, Loic Deleyrolle, Benjamin Lewis, Chenglong Li

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Sustainable foam glass property prediction using machine learning: A comprehensive comparison of predictive methods and techniques by Mohamed Abdellatief, Leong Sing Wong, Norashidah Md Din, Ali Najah Ahmed, Abba Musa Hassan, Zainah Ibrahim, G. Murali, Kim Hung Mo, Ahmed El-Shafie

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Identification of blood plasma protein ratios for distinguishing Alzheimer's disease from healthy controls using machine learning by Ali Safi, Elisa Giunti, Omar Melikechi, Weiming Xia, Noureddine Melikechi

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Corrigendum to “Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees” by Philip H. Williams, Rodney P. Eyles, Georg Weiller

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Enhancing undrained shear strength prediction: a robust hybrid machine learning approach with naïve Bayes modeling by Chen Fang, Ying Li, Yang Shi

“…This paper presents a novel methodology for the USS prediction in soft clays using machine learning techniques, and particularly it highlights the attention on the following five important input variables: pre-consolidation stress (PS), vertical effective stress (VES), liquid limit (LL), plastic limit (PL), and natural water content (W). …”
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Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning by Zhangmu Jing, Yi Zhang, Xiaoling Liu, Qingqian Li, Yanji Hao, Yeqing Li, Hongjie Gao

Subjects: “…Source classifier machine learning…”
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Predicting Risk through Artificial Intelligence Based on Machine Learning Algorithms: A Case of Pakistani Nonfinancial Firms by Shamsa Khalid, Muhammad Anees Khan, M.S. Mazliham, Muhammad Mansoor Alam, Nida Aman, Muhammad Tanvir Taj, Rija Zaka, Muhammad Jehangir

“…So, in this study, we used financial ratios for accurate risk assessment and for the automation of corporate risk management by developing machine learning algorithms using techniques, namely, random forest, decision tree, naïve Bayes, and KNN. …”
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Goal and shot prediction in ball possessions in FIFA Women’s World Cup 2023: a machine learning approach by Iyán Iván-Baragaño, Antonio Ardá, José L. Losada, Rubén Maneiro

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Evaluation of Machine Learning Algorithms for NB-IoT Module Energy Consumption Estimation Based on Radio Channel Quality by Dusan Bortnik, Vladimir Nikic, Srdjan Sobot, Dejan Vukobratovic, Ivan Mezei, Milan Lukic

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Retracted: Evaluation of High-Quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm by International Transactions on Electrical Energy Systems

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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

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Machine learning algorithm for estimating and optimizing the phytochemical content and physicochemical properties of okra slices in an infrared heating system by Hany S. El-Mesery, Ahmed H. ElMesiry, Evans K. Quaye, Zicheng Hu, Ali Salem

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The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses by Liu Jun, Hongguo Li, Yu Mao, Lan Hu, Dan Wu

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A machine learning decision support tool optimizes WGS utilization in a neonatal intensive care unit by Edwin F. Juarez, Bennet Peterson, Erica Sanford Kobayashi, Sheldon Gilmer, Laura E. Tobin, Brandan Schultz, Jerica Lenberg, Jeanne Carroll, Shiyu Bai-Tong, Nathaly M. Sweeney, Curtis Beebe, Lawrence Stewart, Lauren Olsen, Julie Reinke, Elizabeth A. Kiernan, Rebecca Reimers, Kristen Wigby, Chris Tackaberry, Mark Yandell, Charlotte Hobbs, Matthew N. Bainbridge

“…Abstract The Mendelian Phenotype Search Engine (MPSE), a clinical decision support tool using Natural Language Processing and Machine Learning, helped neonatologists expedite decisions to whole genome sequencing (WGS) to diagnose patients in the neonatal intensive care unit. …”
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Design a Robust DDoS Attack Detection and Mitigation Scheme in SDN-Edge-IoT by Leveraging Machine Learning by Habtamu Molla Belachew, Mulatu Yirga Beyene, Abinet Bizuayehu Desta, Behaylu Tadele Alemu, Salahadin Seid Musa, Alemu Jorgi Muhammed

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Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007–2016 by Yu-zhen Zhang, Hai-ying Wu, Run-wei Ma, Bo Feng, Rui Yang, Xiao-gang Chen, Min-xiao Li, Li-ming Cheng

Subjects: “…Machine learning…”
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Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort by Chenyuan Shi, Hanfeng Jiang, Fangzhou Zhao, Yigang Zhang, Haoming Chen

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Improving the Accuracy of Early Detection of Parkinson's Disease Using Brain Signals Based on Feature Selection in Machine Learning by Shamimeh Sadat Nabavi Monfared, Mohammad Reza Yousefi

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An Intelligent System for Classifying Patient Complaints Using Machine Learning and Natural Language Processing: Development and Validation Study by Xiadong Li, Qiang Shu, Canhong Kong, Jinhu Wang, Gang Li, Xin Fang, Xiaomin Lou, Gang Yu

“…ObjectiveThis study aimed to develop and validate an intelligent system for automatically classifying patient complaints using machine learning (ML) and natural language processing (NLP) techniques. …”
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Retracted: Application of Machine Learning in Multi-Directional Model to Follow Solar Energy Using Photo Sensor Matrix by International Journal of Photoenergy

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