AI Machine Learning–Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis by Hocheol Lee, Myung-Bae Park, Young-Joo Won

“… Abstract BackgroundDiabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population. ObjectiveThis study determined diabetes risk factors among older adults aged ≥60 years using machine learning algorithms and selected an optimized prediction model. …”
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Prediction Model for Safe Operation of Pumping Stations Optimized by the Sparrow Search Algorithm and BP Neural Network by Ziwei Yu, Jinhuang Yu, Jinjie Liu, Chenglong Hu, Shengsheng Hu, Junjie Wang, Hehe Zhang, Huiting Lu

“…This model provides a new approach for predicting the safe operation of pumping stations and has particular reference significance for predicting the safe operation of other pumping stations.…”
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Examine the Role of Psychological Resilience in Predicting Social and Professional Performance in Patients with Diabetes, Multiple Sclerosis, and Rheumatism by Ahmad S Alsheikh Al, Ashraf Alqudah

“…Results revealed that psychological resilience positively predicted social and occupational functions among all illnesses. …”
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Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients by Julien Guiot, Monique Henket, Fanny Gester, Béatrice André, Benoit Ernst, Anne-Noelle Frix, Dirk Smeets, Simon Van Eyndhoven, Katerina Antoniou, Lennart Conemans, Janine Gote-Schniering, Hans Slabbynck, Michael Kreuter, Jacobo Sellares, Ioannis Tomos, Guang Yang, Clio Ribbens, Renaud Louis, Vincent Cottin, Sara Tomassetti, Vanessa Smith, Simon L. F. Walsh

“…Specific imaging-based biomarkers associated with the evolution of lung disease are needed to help predict and quantify ILD. Methods We evaluated the potential of an automated ILD quantification system (icolung®) from chest CT scans, to help in quantification and prediction of ILD progression in SSc-ILD. …”
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Prediction of the Stability of the Loaded Rock Based on the Acoustic Emission Characteristics of the Loaded Rock Based on Data Mining by Mengyao Li, Chang Su, Guolong Li

“…Then, based on the AE signal characteristics of the loaded rock, data mining technology is used to construct a model to predict the failure and instability of the loaded rock mass and, finally, verify the reliability of the prediction model based on data mining. …”
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Systemic inflammatory response index improves prognostic predictive value in intensive care unit patients with sepsis by Tuo Xu, Shuaiwei Song, Ke Zhu, Yin Yang, Chengyu Wu, Naixue Wang, Shu Lu

“…The systemic inflammatory response index (SIRI), a new inflammatory indicator, has shown good predictive value in chronic infection, stroke, and cancer. …”
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Machine Learning Approach to Predict the DC Bias for Adaptive OFDM Transmission in Indoor Li-Fi Applications by Marwah T. Salman, David R. Siddle, Amadi G. Udu

“…A robust ML regressor selection process using LazyPredict algorithm (LPA) was employed to identify the optimal regressors for developing the predictive model. …”
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Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania by Ngong'Ho Bujiku Sende, Snehanshu Saha, Leon Ruganzu, Saibal Kar

“…Our policy recommendations draw on the results of the algorithmic predictions.…”
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Predicting and synthesizing terahertz spoof surface plasmon polariton devices with a convolutional neural network model by Vahid Najafy, Bijan Abbasi-Arand, Maryam Hesari-Shermeh

“…This CNN enables the prediction of existing spoof surface plasmon polaritons (SSPPs) and their intensity within a 110% frequency range. …”
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Automated Bitcoin Trading dApp Using Price Prediction from a Deep Learning Model by Zhi Zhan Lua, Chee Kiat Seow, Raymond Ching Bon Chan, Yiyu Cai, Qi Cao

Subjects: “…cryptocurrency price prediction…”
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Assessment of Vitamin D-Binding Protein and Early Prediction of Nephropathy in Type 2 Saudi Diabetic Patients by Manal S. Fawzy, Baraah T. Abu AlSel

“…This study aimed to investigate the potential early prediction role of urinary vitamin D-binding protein (uVDBP) for the diagnosis of DN and to examine the possible correlation to serum VDBP, high-sensitivity C-reactive protein (hs-CRP), and insulin resistance in these patients. …”
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Development and validation of a novel AI-derived index for predicting COPD medical costs in clinical practice by Guan-Heng Liu, Chin-Ling Li, Chih-Yuan Yang, Shih-Feng Liu

“…This study developed and validated an AI-driven COPD Medical Cost Prediction Index (MCPI) to forecast healthcare expenses in COPD patients. …”
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Can Transthoracic Echocardiography Be Used to Predict Fluid Responsiveness in the Critically Ill Patient? A Systematic Review by Justin C. Mandeville, Claire L. Colebourn

“…We systematically evaluated the use of transthoracic echocardiography in the assessment of dynamic markers of preload to predict fluid responsiveness in the critically ill adult patient. …”
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A Dynamic Bayesian Network-Based Real-Time Crash Prediction Model for Urban Elevated Expressway by Xian Liu, Jian Lu, Zeyang Cheng, Xiaochi Ma

“…The results showed that the improved DBN-based RTCPM had better prediction performance than the original DBN-based RTCPM and the MLP based RTCPM. …”
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Studying the effect of heterosis and predicting the prospects of hybrid spring wheat populations in breeding for productivity and drought resistance by L. V. Volkova, O. S. Amunova

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Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment by Stefano Curcio, Alessandra Saraceno, Vincenza Calabrò, Gabriele Iorio

“…The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. …”
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Immune cell profiles and predictive modeling in osteoporotic vertebral fractures using XGBoost machine learning algorithms by Yi-Chou Chen, Hui-Chen Su, Shih-Ming Huang, Ching-Hsiao Yu, Jen-Huei Chang, Yi-Lin Chiu

“…Methods This study aims to investigate the xCell signature-based immune cell profiles in osteoporotic patients with and without vertebral fractures, utilizing advanced predictive modeling through the XGBoost algorithm. Results Our findings reveal an increased presence of CD4 + naïve T cells and central memory T cells in VF patients, indicating distinct adaptive immune responses. …”
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ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction. by Yunyun Dong, Yuanrong Zhang, Yuhua Qian, Yiming Zhao, Ziting Yang, Xiufang Feng

“…Experimental evaluations further illuminate ASGCL's proficiency in predicting drug responses, offering a potent tool for guiding clinical decision-making in cancer therapy.…”
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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review by Md Mohshin Ali, Md. Arif Hossen, Azrina Abd Aziz

“…Emerging Machine learning (ML) techniques have significantly improved the predictive performance and operational efficiency of photocatalytic systems. …”
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Prediction of NOx Emissions from a Direct Injection Diesel Engine Using Artificial Neural Network by J. Mohammadhassani, Sh. Khalilarya, M. Solimanpur, A. Dadvand

“…The results show that the artificial neural network can efficiently be used to predict NOx emissions from the tested engine with about 10% error.…”
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