Enhancing Heart Attack Prediction with Machine Learning: A Study at Jordan University Hospital by Mohammad Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh, Yara Alkayed, Yasmin Al Trabsheh, Bahaaldeen Alshraideh

“…This study uses the Jordan University Hospital (JUH) Heart Dataset to develop and evaluate machine-learning models for predicting heart disease. The primary objective of this study is to enhance prediction accuracy by utilizing a comprehensive approach that includes data preprocessing, feature selection, and model development. …”
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Global surface eddy mixing ellipses: spatio-temporal variability and machine learning prediction by Tian Jing, Ru Chen, Chuanyu Liu, Chunhua Qiu, Chunhua Qiu, Cuicui Zhang, Mei Hong

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Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar by Shiyu Xie, Tao Zhang, Siming You, Santanu Mukherjee, Mingjun Pu, Qing Chen, Yaosheng Wang, Esmat F. Ali, Hamada Abdelrahman, Jörg Rinklebe, Sang Soo Lee, Sabry M. Shaheen

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Probabilistic Forecasts of Storm Sudden Commencements From Interplanetary Shocks Using Machine Learning by A. W. Smith, I. J. Rae, C. Forsyth, D. M. Oliveira, M. P. Freeman, D. R. Jackson

“…Abstract In this study we investigate the ability of several different machine learning models to provide probabilistic predictions as to whether interplanetary shocks observed upstream of the Earth at L1 will lead to immediate (Sudden Commencements, SCs) or longer lasting magnetospheric activity (Storm Sudden Commencements, SSCs). …”
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The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property by Yufeng Qian

“…The present study employs a machine learning-based support vector regression (SVR) method to implement compressive strength prediction. …”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

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Forecasting geothermal temperature in western Yemen with Bayesian-optimized machine learning regression models by Abdulrahman Al-Fakih, Abbas Al-khudafi, Ardiansyah Koeshidayatullah, SanLinn Kaka, Abdelrigeeb Al-Gathe

Subjects: “…Machine learning…”
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Identifying Ocean Submesoscale Activity From Vertical Density Profiles Using Machine Learning by Leyu Yao, John R. Taylor, Dani C. Jones, Scott D. Bachman

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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
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Predicting the delisted companies of Tehran Stock Exchange using machine learning based algorithms by Aminollah Zarghami, Meysam Doaei, Abtin Boostani

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Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

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Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia. by Daniel R Schrider, Julien Ayroles, Daniel R Matute, Andrew D Kern

“…We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. …”
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Dynamic Interferometry for Freeform Surface Measurement Based on Machine Learning-Configured Deformable Mirror by Xu Chang, Yao Hu, Jintao Wang, Xiang Liu, Qun Hao

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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

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Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review by Taseef Hasan Farook, Nafij Bin Jamayet, Johari Yap Abdullah, Mohammad Khursheed Alam

“…GRADE approach revealed serious risks of bias and inconsistencies with most studies containing more positive cases than their true prevalence in order to facilitate machine learning. Patient-perceived symptoms and clinical history were generally found to be less reliable than radiographs or histology for training accurate machine learning models. …”
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COVID-19 World Vaccine Adverse Reactions Based on Machine Learning Clustering Algorithm by Lozan M. Abdulrahman, Adnan Mohsin Abdulazeez, Dathar A. Hasan

Subjects: “…COVID-19 Vaccine Reactions, Machine Learning, Clustering Algorithm, VARSE, Weka…”
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Robust analysis of photovoltaic plants: A framework based on prediction uncertainties by machine learning by Seyyed Shahabaddin Hosseini Dehshiri, Bahar Firoozabadi

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Enabling smart parking for smart cities using Internet of Things (IoT) and machine learning by Mofadal Alymani, Lenah Abdulaziz Almoqhem, Dhuha Ahmed Alabdulwahab, Abdulrahman Abdullah Alghamdi, Hussain Alshahrani, Khalid Raza

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Lunar Calendar Usage to Improve Forecasting Accuracy Rainfall via Machine Learning Methods by Gumgum Darmawan, Gatot Riwi Setyanto, Defi Yusti Faidah, Budhi Handoko

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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

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