A machine-learning-based hardware-Trojan detection approach for chips in the Internet of Things by Chen Dong, Jinghui Chen, Wenzhong Guo, Jian Zou

“…In this study, we propose a machine-learning-based hardware-Trojan detection method at the gate level. …”
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A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel by Ngoc-Long Tran, Trong-Ha Nguyen, Van-Tien Phan, Duy-Duan Nguyen

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Design of an Early Prediction Model for Parkinson’s Disease Using Machine Learning by K. Velu, N. Jaisankar

“…In literature, diverse Machine Learning models are employed for Parkinson’s disease diagnosis utilizing voice analysis. …”
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Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms by Zhichao Wang, Long Cheng, Guanghui Li, Huiyan Cheng

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Early Detection of Seasonal Outbreaks from Twitter Data Using Machine Learning Approaches by Samina Amin, Muhammad Irfan Uddin, Duaa H. alSaeed, Atif Khan, Muhammad Adnan

“…This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest (RF), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree (DT), with the help of Term Frequency and Inverse Document Frequency (TF-IDF). …”
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Fully automated segmentation and classification of renal tumors on CT scans via machine learning by Jang Hee Han, Byung Woo Kim, Taek Min Kim, Ji Yeon Ko, Seung Jae Choi, Minho Kang, Sang Youn Kim, Jeong Yeon Cho, Ja Hyeon Ku, Cheol Kwak, Young-Gon Kim, Chang Wook Jeong

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Optimal Scheduling Model of WDM/OTN Network Transmission Line Based on Machine Learning by Jianhua Zhao, Jingquan Li, Huicong Fan, Wenxiao Li, Jingna Zhang, Xiaoyuan Dai

“…In order to solve the problem that the influencing factors are difficult to parameterize in the design and development of WDM/OTN backbone network routing planning tools, the author proposes an optimal scheduling model for WDM/OTN network transmission lines based on machine learning. Using the machine learning classification algorithm as a tool, the weight coefficients of each constraint factor are extracted from the historical design decisions, and the routing parameter model is constructed, so as to realize the intelligent routing selection, through actual simulation analysis and engineering verification. …”
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Machine learning approaches for predicting protein-ligand binding sites from sequence data by Orhun Vural, Leon Jololian

“…This paper reviews studies that use machine learning to predict protein-ligand binding sites from sequence data, focusing on recent advancements. …”
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Detecting respiratory diseases using machine learning-based pattern recognition on spirometry data by Ahmed I. Taloba, R.T. Matoog

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Impact of Climate Change and Air Pollution Forecasting Using Machine Learning Techniques in Bishkek by Erkin Isaev, Boobek Ajikeev, Urmatbek Shamyrkanov, Kenjebek-uulu Kalnur, Karimov Maisalbek, Roy C. Sidle

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Retracted: A System of Remote Patients’ Monitoring and Alerting Using the Machine Learning Technique by Journal of Food Quality

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Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis by Antonios Georgas, Anna Panagiotakopoulou, Grigorios Bitsikas, Katerina Vlantoni, Angelo Ferraro, Evangelos Hristoforou

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The Relationship Between Consumption Power and GDP Growth in China and Machine Learning Prediction Analysis by Hu Runsong

“…The paper examines the use of machine learning for predicting consumption capacity by integrating various economic models, including Support Vector Regression (SVR) and Long Short-Term Memory Network (LSTM). …”
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Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach by Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

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Application of the Different Machine Learning Algorithms to Predict Dry Matter Intake in Feedlot Cattle by Hayati Köknaroğlu, Özgür Koşkan, Malik Ergin

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Machine learning for the diagnosis accuracy of bipolar disorder: a systematic review and meta-analysis by Yi Pan, Pushi Wang, Bowen Xue, Yanbin Liu, Xinhua Shen, Shiliang Wang, Xing Wang

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Sarcasm Text Detection on News Headlines Using Novel Hybrid Machine Learning Techniques by Neha Singh, Umesh Chandra Jaiswal

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Enhancing thyroid disease prediction and comorbidity management through advanced machine learning frameworks by P. Sanju, N. Syed Siraj Ahmed, P. Ramachandran, P. Mohamed Sajid, R. Jayanthi

Subjects: “…Machine learning…”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“… BackgroundAlthough catheter ablation (CA) is currently the most effective clinical treatment for atrial fibrillation, its variable therapeutic effects among different patients present numerous problems. Machine learning (ML) shows promising potential in optimizing the management and clinical outcomes of patients undergoing atrial fibrillation CA (AFCA). …”
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Hybridization of stochastic hydrological models and machine learning methods for improving rainfall-runoff modeling by Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick K. Ronoh, Stephen E. Moore

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