How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms by Sophie G. Zaloumis, Megha Rajasekhar, Julie A. Simpson

“…Abstract Background Machine learning algorithms have been used to predict malaria risk and severity, identify immunity biomarkers for malaria vaccine candidates, and determine molecular biomarkers of antimalarial drug resistance. …”
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ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…Scientific contribution A comprehensive validation of various machine learning algorithms combined with diverse molecular representations on a large dataset for predicting Caco-2 permeability was reported. …”
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Improving Transformer Health Index Prediction Performance Using Machine Learning Algorithms with a Synthetic Minority Oversampling Technique by Muhammad Akmal A. Putra, Suwarno, Rahman Azis Prasojo

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Prediction of asthma outpatients using cumulative particulate matter and machine learning algorithms: a case study in Adiyaman, Turkey by Abdurrahman Özbeyaz, Mustafa Yıldırım, Fatih Tufaner

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Development and validation of a biomarker-based prediction model for metastasis in patients with colorectal cancer: Application of machine learning algorithms by Erfan Ayubi, Sajjad Farashi, Leili Tapak, Saeid Afshar

“…The predictive performance of the algorithm with the highest accuracy was then externally validated on the GSE41568 dataset. …”
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Evaluating machine learning algorithms for predicting HIV status among young Thai men who have sex with men by Krittaka Soha, Sadiporn Phuthomdee, Thanapat Srichai, Lanchakorn Kittiratanawasin, Win Min Han, Sirinya Teeraananchai

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Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms by Mehmet Eroğlu, Ali Osman Turgut, Mürsel Küçük, Muhammed Furkan Önen

“…Objective This study aimed to investigate the performance of different machine learning algorithms in predicting weaning weight based on biometric measurements of Romanov lambs at 30 days of age. …”
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Predicting response to anti-VEGF therapy in neovascular age-related macular degeneration using random forest and SHAP algorithms by Peng Zhang, Jialiang Duan, Caixia Wang, Xuejing Li, Jing Su, Qingli Shang

“…Purpose: This study aimed to establish and validate a prediction model based on machine learning methods and SHAP algorithm to predict response to anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration (AMD). …”
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An Overview of Remaining Useful Life Prediction of Battery Using Deep Learning and Ensemble Learning Algorithms on Data-Dependent Models by Sravanthi C. L., Chandra Sekhar J. N., N. Chinna Alluraiah, Dhanamjayulu C., Harish Kumar Pujari, Baseem Khan

“…This article classifies and summarises the RUL prediction by data-dependent models using machine learning (ML), deep learning (DL) and ensemble learning (EL) algorithms suggested in a last few years. …”
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Use of machine learning algorithms to predict outcomes among frail patients undergoing percutaneous coronary intervention: Are we there yet? by Josip Andelo Borovac, Mihajlo Kovacic, Stefan Harb

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Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods by Babak Pourakbari, Setareh Mamishi, Sepideh Keshavarz Valian, Shima Mahmoudi, Reihaneh Hosseinpour Sadeghi, Mohammad Reza Abdolsalehi, Mahmoud Khodabandeh, Mohammad Farahmand

“…This study evaluates the performance of machine learning algorithms in predicting disease severity among pediatrics. …”
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Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms by Muhammad Sya'ban Harahap, Alva Hendi Muhammad

“…This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. …”
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Predicting indoor temperature of solar green house by machine learning algorithms: A comparative analysis and a practical approach by Wenhe Liu, Tao Han, Cong Wang, Feng Zhang, Zhanyang Xu

“…This study focuses on a solar greenhouse located at the experimental base of Shenyang Agricultural University in Shenyang, Liaoning Province, to develop multi-step temperature prediction models based on machine learning algorithms. …”
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Chemometric and meta-heuristic algorithms to find optimal wavelengths and predict ‘Red Delicious’ apples traits using Vis-NIR by Mahsa S. Razavi, Vali Rasouli Sharabiani, Mohammad Tahmasebi, Silvia Grassi, Mariusz Szymanek

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The impact of intravenous iodinated contrast agents on radiotherapy dose calculation and radiobiological effect predictions in central lung cancer by Defu Yang, Feng Shang, Ying Xu, Ying Yan

“…This study evaluates and compares dosimetric differences and predictions of Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) between the Analytic Anisotropic Algorithm (AAA) and Acuros XB (AXB) algorithm in lung cancer radiotherapy, under both contrast-enhanced and non-contrast enhanced CT conditions.MethodsTwenty patients with centralized lung cancer treated with intensity-modulated radiation therapy (IMRT) technique, including two patients with small cell lung cancer and 18 with non-small cell lung cancer, were selected to undergo CT scanning with and without contrast. …”
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A Finite Control Set Model Predictive Control Algorithm With Low Complexity for Neutral-Point Clamped Converters With Switching Constraints by Dimas A. Schuetz, Fernanda de M. Carnielutti, Mokhtar Aly, Margarita Norambuena, Jose Rodriguez, Humberto Pinheiro

“…This paper proposes a Finite Control Set Model Predictive Control algorithm with low complexity for three-phase grid-tied Neutral-Point Clamped converters with switching constraints. …”
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A Hierarchical Control Algorithm for a Pursuit–Evasion Game Based on Fuzzy Actor–Critic Learning and Model Predictive Control by Penglin Hu, Chunhui Zhao, Quan Pan

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Development and Validation of a Machine Learning Model for Early Prediction of Sepsis Onset in Hospital Inpatients from All Departments by Pierre-Elliott Thiboud, Quentin François, Cécile Faure, Gilles Chaufferin, Barthélémy Arribe, Nicolas Ettahar

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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS by Viacheslav Osadchyi, Maksym Pavlenko, Liliia Pavlenko, Oleksii Sysoiev, Vladyslav Kruglyk

“…These changes significantly influence the formation of predictive competence – a crucial human capacity for reasoned forecasting and decision-making under uncertainty. …”
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Revisiting Online Algorithms: A Survey of Set Cover Solutions Beyond Competitive Analysis by Christine Markarian, Claude Fachkha, Noura Yassine

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