Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms by Haobo Kong, Yong Li, Ya Shen, Jingjing Pan, Min Liang, Zhi Geng, Yanbei Zhang

“…Abstract Background This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms. …”
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Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis by Masoumeh Vali, Hossein Motahari Nezhad, Levente Kovacs, Amir H Gandomi

“…Tree-based models were the primarily used algorithms and showed promising results in predicting PTSD outcomes for various groups, as indicated by their pooled AUCs: military incidents (0.745), sexual or physical trauma (0.861), natural disasters (0.771), medical trauma (0.808), firefighters (0.96), and alcohol-related stress (0.935). …”
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On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…This study aims to predict the shear strength of reinforced concrete (RC) deep beams based on artificial neural network (ANN) using four training algorithms, namely, Levenberg–Marquardt (ANN-LM), quasi-Newton method (ANN-QN), conjugate gradient (ANN-CG), and gradient descent (ANN-GD). …”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…A user-friendly interface was developed for instant SE prediction of carbon fiber reinforced mortar, requiring only essential input parameters.…”
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Comparative analysis of regression algorithms for drug response prediction using GDSC dataset by Soojung Ha, Juho Park, Kyuri Jo

“…In addition, it is difficult for researchers to know which algorithm is appropriate for prediction as various regression and feature selection algorithms exist. …”
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Predicting diabetes using supervised machine learning algorithms on E-health records by Sulaiman Afolabi, Nurudeen Ajadi, Afeez Jimoh, Ibrahim Adenekan

“…The research explores the effectiveness of three supervised machine learning algorithms: logistic regression, Random Forest, and k-nearest neighbors (KNN), in developing predictive models for diabetes. …”
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Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection by Omar Farhan Al-Hardanee, Hüseyin Demirel

“…In this study, artificial neural network algorithms (RNN and LSTM) are used to predict the condition of the hydropower station, identify the fault before it occurs, and avoid it. …”
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Predicting the Classification of Heart Failure Patients Using Optimized Machine Learning Algorithms by Marzia Ahmed, Mohd Herwan Sulaiman, Md Maruf Hassan, Touhid Bhuiyan

Subjects: “…Heart failure survival prediction…”
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Experiments on software error prediction using Decision Tree and Random Forest algorithms by Ilona Bluemke, Paweł Borsukiewicz

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Performance and improvement of deep learning algorithms based on LSTM in traffic flow prediction by Wei Xu, Eric Blancaflor, Mideth Abisado

“…This paper introduces an improved LSTM (Long Short-Term Memory) algorithm and sliding window technology to improve the accuracy and stability of traffic flow prediction. …”
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Flood Area Prediction using a Stacked Ensemble of Tree-Based Algorithms by Olusogo Julius Adetunji

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Comparative Analysis of Linear Regression and Neural Network Algorithms for Stock Price Prediction by Eldrianto Christian Wibowo, Ariya Dwika Cahyono

“…This study compares the performance of Linear Regression and Neural Network algorithms in predicting stock prices using historical data from PT Bank Central Asia Tbk (BBCA) for the period from January 1, 2019, to February 17, 2025. …”
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Leveraging ECG images for predicting ejection fraction using machine learning algorithms by Abhyuday Kumara Swamy, Vivek Rajagopal, Deepak Krishnan, Paramita Auddya Ghorai, Anagha Choukhande, Santhosh Rathnam Palani, Deepak Padmanabhan, Emmanuel Rupert, Devi Prasad Shetty, Pradeep Narayan

“…Introduction: The capability to accurately predict the ejection fraction (EF) from an electrocardiogram (ECG) holds significant and valuable clinical implications. …”
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Utilization of Classification Learning Algorithms for Upper-Body Non-Cyclic Motion Prediction by Bon H. Koo, Ho Chit Siu, Dava J. Newman, Ellen T. Roche, Lonnie G. Petersen

“…This study explores two methods of predicting non-cyclic upper-body motions using classification algorithms. …”
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Comparative analysis of machine learning algorithms for predicting depression among individuals with diabetes by Hind Bourkhime, Noura Qarmiche, Soumaya Benmaamar, Nada Lazar, Mohammed Omari, Mohamed Berraho, Nabil Tachfouti, Samira El Fakir, Hanan El Ouahabi, Nada Otmani

“…This research study presents a comprehensive comparative analysis of eight distinct machine learning (ML) algorithms to predict depression among individuals with diabetes. …”
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Integrating evolutionary algorithms and enhanced-YOLOv8 + for comprehensive apple ripeness prediction by Yuchi Li, Zhigao Wang, Aiwei Yang, Xiaoqi Yu

“…For structured text data, support vector regression (SVR) models optimized using the Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA) were utilized to predict apple ripeness, with the WOA-optimized SVR demonstrating exceptional generalization capabilities. …”
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Prediction models based on machine learning algorithms for COVID-19 severity risk by Hansong Zhang, Ying Wang, Yan Xie, Cuihan Wang, Yuqi Ma, Xin Jin

Subjects: “…Prediction models…”
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Predicting Dilution in Underground Mines with Stacking Artificial Intelligence Models and Genetic Algorithms by Jorge L. V. Mariz, Tertius S. G. Ferraz, Marinésio P. Lima, Ricardo M. A. Silva, Hyongdoo Jang

“…This study introduces a statistically rigorous methodology for the prediction of dilution in underground mining operations. …”
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Car Price Prediction and Recognition Using Deep Learning and Computer Vision Algorithms by Hira Farman, Saad Ahmed, Muhammad Hussain Mughal, Qurat -ul-ain Mastoi, Govari Shankar Lalwani

“…Along with the outcomes of the experiments in this study. In order to predict the resale price of used cars given a number of parameters, such as the car's model, year of production, mark, selling type, fuel type, and current pricing, a variety of regression algorithms based on supervised machine learning were utilized in this study. …”
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Evaluation of machine learning and deep learning algorithms for fire prediction in Southeast Asia by Aditya Eaturu, Krishna Prasad Vadrevu

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