Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

“…This paper analyses the suitability of several machine learning algorithms for CKD prediction in consideration of health-related parameters like age, blood pressure, and blood glucose levels. …”
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A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…However, a stacking architecture can solve this problem by combining distinct algorithms and models. This study compares the performance of traditional time series models and deep learning algorithms in malaria case prediction and explores the application value of stacking methods in the field of infectious disease prediction.…”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Artificial intelligence algorithms can be continuously optimized based on prior knowledge and real-time data, which significantly improves the prediction efficiency of antibacterial peptides and reduces research and development costs. …”
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Retracted: Water Quality Prediction Using Artificial Intelligence Algorithms by Applied Bionics and Biomechanics

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Predicting Quail Egg Quality Using Machine Learning Algorithms by BI Yildiz, K Eskioğlu, D Özdemir, M Akşit

“…ABSTRACT This study evaluates the effectiveness of machine learning algorithms in predicting quail egg quality based on nine key parameters, including egg weight, egg width, egg length, yolk height, yolk width, yolk weight, albumen height, albumen width, and albumen length. …”
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Dynamically Predicting the Quality of Service: Batch, Online, and Hybrid Algorithms by Ya Chen, Zhong-an Jiang

“…A general system architecture for such systems continuously collects the user-service invocation records and includes both an online training module and an offline training module for quality prediction. In addition, we introduce matrix factorization-based online and offline training algorithms based on the gradient descent algorithms and demonstrate the fitness of this online/offline algorithm framework to the proposed architecture. …”
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Machine Learning Algorithms in Predicting Prices in Volatile Cryptocurrency Markets by Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez

“…This study aims to develop a predictive model for cryptocurrency prices in highly volatile markets. …”
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Comparing text classification algorithms with n-grams for mediation prediction by Retzi Y. Lewu, Kusrini Kusrini, Ainul Yaqin

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Advancing wildfire prediction in Nepal using machine learning algorithms by Saugat Sapkota, Khagendra Prasad Joshi, Sajesh Kuikel, Dipesh Kuinkel, Biplov Bhandari, Yanhong Wu, Haijian Bing, Suresh Marahatta, Deepak Aryal, S-Y Simon Wang, Binod Pokharel

“…To improve wildfire prediction and preparedness, this study evaluated four advanced machine learning algorithms—Random Forest, Radial Basis Function Neural Network, Artificial Neural Network, and Support Vector Machine—using comprehensive dataset (2001–2023) of meteorological, topographical, anthropogenic, locational, and vegetation variables. …”
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Prediction of high-risk pregnancy based on machine learning algorithms by Xinyu Pi, Junzhi Wang, Liangliang Chu, Guochun Zhang, Wenli Zhang

“…Abstract This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. …”
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Ensemble Learning Algorithms based on Road Accident Data Prediction by Reddy Gondi Konda, Vullam Nagagopi Raju, Sekhar G. Soma, Sundaragiri Dheeraj, Shaik Subhani

“…Due to this classification system to implement of safety measures and accident prediction. Different types of elements like weather, road conditions, lighting, and vehicle conditions are used to predict road accidents. …”
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Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

“…Therefore, this study aims to predict mung bean production using a machine learning algorithm. …”
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Investigating of Machine Learning Based Algorithms for Liver Cirrhosis Prediction by Young Choi, Eunsung Oh

“…This paper presents a study on utilizing machine learning algorithms for predicting liver cirrhosis with a focus on enhancing accuracy rates. …”
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Predicting Scientific Research Impacts in Biotechnology by Machine Learning Algorithms by Ghasem Azadi Ahmadabadi

Subjects: “…predicting research impact…”
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An Investigation on Prediction of Infrastructure Asset Defect with CNN and ViT Algorithms by Nam Lethanh, Tu Anh Trinh, Mir Tahmid Hossain

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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

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Machine Learning Predictive Models for Survival in Patients with Brain Stroke by Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi

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Comparative Analysis of Supervised Machine Learning Algorithms for COVID-19 Prediction by Rubina Shaheen, Beenish Akram, Amna Zafar, Talha Waheed

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Design and analysis of active queue management algorithm based on predictive control by WANG Ping, CHEN Hong, LU Xiao-hui

“…Model predictive control as a novel active queue management（AQM） algorithm was proposed for Internet system with large delay,called MPAQM.Considering the causality of time-delay system,the predicted output was defined.Then,the control requirement was converted to the optimal control objective,and the drop probability was obtained by solving the optimal problem.Furthermore,the delay-independent stability condition of closed-loop system was derived,which gave the guidelines how to select the parameters of MPAQM algorithm to assure the stability and fast convergence of the network system.The performances of MPAQM were evaluated through a series of simulations in NS2 under the single/multiple topology.The simulation results show that the queue length with MPAQM algorithm reaches the desired value with minimal tracking error and lower drop probability.MPAQM algorithm outperforms RED,PI and SPI-RED algorithms in terms of disturbance rejection,stability,and robustness.…”
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Complex Network Algorithm for Glossary Formation Context-Related Predictive Terms by Oleg Popov, Adrian Grosu, Sergey Kramarov

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