Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets by Inam Abousaber, Haitham F. Abdallah, Hany El-Ghaish

“…However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.MethodsA novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed. …”
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Deep learning-driven approach for cataract management: towards precise identification and predictive analytics by Shuaixin Lu, Lingling Ba, Jie Wang, Min Zhou, Peiyao Huang, Xiaohua Zhang, Simo Pan, Xinmiao Zhou, Kai Wen, Jing Sun

“…DL could optimize the intraocular lens (IOL) power calculation, predict the risk of complications and long-term surgery requirements. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…To address this challenge, model predictive control based on artificial neural networks can be employed. …”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…In recent years, the rapid development of artificial intelligence has opened up a new opportunity for data prediction. In this study, utilizing the EGM2008 satellite gravity model, we conducted a comprehensive analysis of three machine learning algorithms—random forest, support vector machine, and recurrent neural network—and compared their performances against the traditional Kriging interpolation method. …”
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Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives by Vishnu Priya Veeraraghavan, Shikhar Daniel, Arun Kumar Dasari, Kaladhar Reddy Aileni, Chaitra patil, Santosh R. Patil

“…Various AI algorithms, including supervised learning, unsupervised learning, and deep learning approaches, have been discussed in the context of oral cancer prediction. …”
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Modeling and computing experiment in the problem of predicting the per capita monetary income of the population based on the methods of correlation and regression analysis by Angelina Vladimirovna Vaskina, Victoria Igorevna Naats

“…The numerical calculations are accompanied by statistical evaluations of predictive performance of the considered mathematical model, performed the analysis and discussion of the results. …”
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Pavement performance model for road maintenance and repair planning: a review of predictive techniques by Krishna Singh Basnet, Jagat Kumar Shrestha, Rabindra Nath Shrestha

“…This paper provides a review of predictive analytics for roads, identifying gaps and limitations in current methodologies. …”
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Corrosion Risk Assessment in Coastal Environments Using Machine Learning-Based Predictive Models by Marta Terrados-Cristos, Marina Diaz-Piloneta, Francisco Ortega-Fernández, Gemma Marta Martinez-Huerta, José Valeriano Alvarez-Cabal

“…Among the models tested, tree-based algorithms, particularly gradient boosting, provided the highest prediction accuracy (F1 score: 0.8673). …”
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Predictive modeling of punchouts in continuously reinforced concrete pavement: a machine learning approach by Ghazi Al-Khateeb, Ali Alnaqbi, Waleed Zeiada

“…In this study, a comprehensive approach that integrates descriptive statistics, correlation analysis, and machine learning algorithms is employed to develop models and predict punchouts in CRCP. …”
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A predictive healthcare model using machine learning and psychological factors for medication adherence by Junwu Dong, Minyi Chu, Yirou Xu

“…This study aims to develop a predictive model for medication adherence behaviour (MAB) employing machine learning techniques, addressing the limitations of traditional correlation-based approaches. …”
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A robust and statistical analyzed predictive model for drug toxicity using machine learning by Deepak Rawat, Rohit Bajaj, Rachit Manchanda, Ankush Mehta, Prabhu Paramasivam, Suraj Kumar Bhagat, Abinet Gosaye Ayanie

“…Abstract Over the years, toxicity prediction has been a challenging task. Artificial intelligence and machine learning provide a platform to study toxicity prediction more accurately with a reduced time span. …”
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Assistance algorithm of nursing for amiodarone intravenous infusion by Francimar Tinoco de Oliveira, Graciele Oroski Paes, Maria Gefé da Rosa Mesquita, Victor Magalhães de Paula Souza, Elaine dos Santos Carlos, Caroline Scantamburlo Martins

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Assistance algorithm of nursing for amiodarone intravenous infusion by Francimar Tinoco de Oliveira, Graciele Oroski Paes, Maria Gefé da Rosa Mesquita, Victor Magalhães de Paula Souza, Elaine dos Santos Carlos, Caroline Scantamburlo Martins

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Predictive modeling of gestational weight gain: a machine learning multiclass classification study by Audêncio Victor, Hellen Geremias dos Santos, Gabriel Ferreira Santos Silva, Fabiano Barcellos Filho, Alexandre de Fátima Cobre, Liania A. Luzia, Patrícia H.C. Rondó, Alexandre Dias Porto Chiavegatto Filho

“…This study aims to develop and evaluate machine learning models to predict GWG categories: below, within, or above recommended guidelines. …”
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Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…The second model predicts the transition from multiple AAb+ to the onset of T1D. …”
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Analysis of the 10-day ultra-marathon using a predictive XG boost model by Beat Knechtle, Elias Villiger, David Valero, Lorin Braschler, Katja Weiss, Rodrigo Luiz Vancini, Marilia S. Andrade, Volker Scheer, Pantelis T. Nikolaidis, Ivan Cuk, Thomas Rosemann, Mabliny Thuany

“…A machine learning model based on the XG Boost algorithm was built to predict running speed from the athlete´s age, gender, country of origin, country where the race takes place, the type of race and the kind of running surface. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Leveraging the Coxboost and random survival forest combination algorithm, we filtered out six DC-related genes on which a prognostic prediction model, DCRGS, was established. …”
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A Predictive Model for Secondary Posttonsillectomy Hemorrhage in Pediatric Patients: An 8‐Year Retrospective Study by Yuting Ge, Wenchuan Chang, Lixiao Xie, Yan Gao, Yue Xu, Huie Zhu

“…Multivariate logistic regression and seven machine learning algorithms were used to construct predictive models. …”
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Stock Price Pattern Prediction Based on Complex Network and Machine Learning by Hongduo Cao, Tiantian Lin, Ying Li, Hanyu Zhang

“…In general, the prediction ability of SVM algorithms is better than that of KNN algorithms.…”
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Early Risk Prediction in Acute Aortic Syndrome on Clinical Data Using Machine Learning by Mehdi Tavafi, Kalpdrum Passi, Robert Ohle

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