Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…The GWO-SVM-SG1st model achieved the highest classification accuracy, with 94.641% on the prediction sets. This study showcases the potential of combining hyperspectral imaging with intelligent optimization algorithms, offering an effective solution for jujube variety classification.…”
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Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

Subjects: “…TN prediction…”
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A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms by Aihua Yu, Qingjie Xiao

“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. …”
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Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation by Hutan Ashrafian, Jessica Morley, Joe Zhang, Christopher Oddy

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Learning unbiased risk prediction based algorithms in healthcare: A case study with primary care patients by Vibhuti Gupta, Julian Broughton, Ange Rukundo, Lubna J. Pinky

“…Additionally, effective strategies are proposed to address gender, race, and age biases, ensuring that risk prediction outcomes are equitable and impartial. Through experiments with various machine learning algorithms leveraging the Fairlearn tool, we have identified biases in the dataset, compared the impact of these biases on the prediction performance, and proposed effective strategies to mitigate these biases. …”
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WCN25-867 BAYESIAN DEEP LEARNING ALGORITHMS TO PREDICT THE RATE OF DETERIORATION IN CHRONIC KIDNEY DISEASE by Laxmi Priya Kasi, Sujoy Kar, Sanjay Maitra, Tameem Ansari, Bharath Potla, Sangita Reddy

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Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea) by Degninou Yehadji, Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo

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PM2.5 concentration prediction using machine learning algorithms: an approach to virtual monitoring stations by Ahmad Makhdoomi, Maryam Sarkhosh, Somayyeh Ziaei

“…In this research, an attempt has been made to predict the concentrations of PM2.5 using four Machine Learning (ML) models. …”
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Use of responsible artificial intelligence to predict health insurance claims in the USA using machine learning algorithms by Ashrafe Alam, Victor R. Prybutok

“…Methods: Six ML algorithms were used to predict health insurance claims, and their performance was evaluated using various metrics. …”
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Leveraging Machine Learning Regression Algorithms to Predict Mechanical Properties of Evaporitic Rocks From Their Physical Attributes by Ayham Zaitouny, Hasan Arman, Anusuya Krishnan, Alaa Ahmed, Ahmed Gad

“…In this study, machine learning (ML) regression algorithms were applied to predict four key mechanical parameters, namely, uniaxial compressive strength (UCS), point load index (PLI), indirect tensile strength (ITS), and Schmidt hardness value (SHV), based on the physical attributes of evaporitic rocks. …”
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The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms by Hongxia Yan, Yixin Tan, Fan Qiao, Zhuotong Zeng, Yaqian Shi, Xueqin Zhang, Lu Li, Ting Zeng, Yi Zhan, Ruixuan You, Xinglan He, Rong Xiao, Xiangning Qiu

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Location, Location, Location: The Power of Neighborhoods for Apartment Price Predictions Based on Transaction Data by Christopher Kmen, Gerhard Navratil, Ioannis Giannopoulos

Subjects: “…real estate price prediction…”
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Human-Centred Design Meets AI-Driven Algorithms: Comparative Analysis of Political Campaign Branding in the Harris–Trump Presidential Campaigns by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

“…Utilising a mixed-methods approach, we integrated quantitative analysis employing AI’s eye-tracking consumer behaviour metrics (Predict, trained on 180,000 screenings) with an AI-LLM neuroscience-based marketing assistant (CoPilot), with 67,429 areas of interest (AOIs). …”
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A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

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PREDICTION OF THE POOR RATE K-MEANS AND GENERALIZED REGRESSION NEURAL NETWORK ALGORITHMS (CASE STUDY: NORTH SUMATRA PROVINCE) by Nita Suryani, Arnita Arnita, Rinjani Cyra Nabila, Amanda Fitria

“…In this study, poverty levels were mapped using the K-Means algorithm, and GRNN was then utilized for modeling and prediction. …”
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Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

“…Classification axioms can be formed by 1-class learning procedures for the predictive state evaluation of subsequent production start-ups based on collected machine and process data from past production start-ups. …”
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Coordinative Two-Stage Superheated Steam Temperature Linkage Control Based on Multivariable Generalized Predictive Control Algorithm by Sheng TONG, Le LIU, Pengfei WANG

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Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…A Bland-Altman plot of the differences between the predicted values and the assessment values showed 95% of them within 0.21 WTE per patient. …”
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