Hyperbox Mixture Regression for process performance prediction in antibody production by Ali Nik-Khorasani, Thanh Tung Khuat, Bogdan Gabrys

“…This paper addresses the challenges of predicting bioprocess performance, particularly in monoclonal antibody (mAb) production, where conventional statistical methods often fall short due to time-series data’s complexity and high dimensionality. …”
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Predict the writer’s trait emotional intelligence from reproduced calligraphy by Ruimin Lyu, Wen Sun, Yongle Cheng, Yifei Shi, Ning Wang, Joydeep Bhattacharya, Guoying Yang

“…A Siamese neural network was then used to extract deep feature differences between the reproduction characters and the reference characters, which were further combined with handcrafted features for regression-based predictions. Experimental results show that, using Mean Absolute Error (MAE), Mean Squared Error (MSE) and Pearson Correlation Coefficient (PCC) as evaluation metrics, this method’s ability to predict the writer’s trait EI from calligraphy reproductions (MAE: 0.463, MSE: 0.462, PCC: 0.730) significantly outperforms human evaluative abilities (MAE: 1.006, MSE: 1.740, PCC: 0.145), confirming that calligraphy reproductions indeed contain latent information about the writer’s trait EI.…”
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Graph neural network-based drug-drug interaction prediction by Khushnood Abbas, Chen Hao, Xu Yong, Mohammad Kamrul Hasan, Shayla Islam, Abdul Hadi Abd Rahman

“…Thus, the accurate prediction of DDIs is paramount. Building on recent advancements in graph neural network (GNN) architectures, this paper extends prior research, such as the SAGE GNN model, Graph Attention Network model, and Graph Diffusion Network model, by integrating advanced techniques such as skip connections, post-processing layers, and optimized training methods. …”
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Zero-Shot Prediction of Conversational Derailment With Large Language Models by Kenya Nonaka, Mitsuo Yoshida

“…To address this challenge, we focus on the zero-shot performance of large language models (LLMs), which have advanced rapidly in recent years. This study aims to evaluate the zero-shot prediction performance of conversational derailment using LLMs. …”
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Inferior Mesenteric Artery Associated Type II Endoleaks: Are They Predictable? by Harun Jalil, Syed Mahmood, Iftikhar Zaman, Asaad Osman, Syed Mustafa, Abdullah Saeed

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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

“…In order to solve the problem of difficulty in learning semantic pattern representations between user dynamic interest sequences using path based and knowledge graph based entity embedding methods, the author proposes research on spatiotemporal data modeling and prediction algorithms in intelligent management systems. …”
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Empirical Bayes Prediction for an Attribute Control Chart in Quality Monitoring by Yadpirun Supharakonsakun

“…To calculate the control limits, the posterior distribution and the predictive density are derived for the unconditional predictive density of the run length. …”
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Prediction of success in assisted reproductive technology with the help of morphology of the testis by N. G. Kulchenko

“…The question of the chances of spermatogenesis recovery and increased probability of sperm extraction in repeated assisted reproductive technology (ART) programs is important for both the doctor and the patient.Purpose. To evaluate the morphological changes of spermatogenic epithelium in patients with male infertility in terms of prognosis of ART success.Patients and methods. 264 men with infertility were examined. …”
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Prediction of hepatitis-C virus using statistical learning models by Shalini Kumari, Subhajit Das, Prashant Kumar Sonker, Agni Saroj, Mukesh Kumar

“…The analytical methods have improved the overall predictive accuracy for HCV infection and will aid in the early identification of the disease. …”
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Anthropometric indexes for predicting high blood pressure in Turkish adults by Burcu Aksoy Canyolu, Nilüfer Şen, Beste Özben Sadıç

“…Purpose: It is controversial which anthropometric indexes are the best in predicting the risk of hypertension and how anthropometric measurements are related to blood pressure (BP). …”
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Prediction of electrical load demand using combined LHS with ANFIS. by Ahmed G Ismail, Sayed H A Elbanna, Hassan S Mohamed

“…Comparative analysis investigates performing various machine learning models, including Adaptive Neuro-Fuzzy Inference Systems (ANFIS) alone, and ANFIS combined with Latin Hypercube sampling (LHS), in predicting electrical load demand. The paper explores enhancing ANFIS through LHS compared with Monte Carlo (MC) method to improve predictive accuracy. …”
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Recent advances in explainable Machine Learning models for wildfire prediction by Abira Sengupta, Brendon J. Woodford

“…Machine Learning (ML) and Artificial Intelligence models have emerged to predict both the onset of wildfires and evaluate the extent of damage a wildfire would cause. …”
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Predicting retracted research: a dataset and machine learning approaches by Aaron H. A. Fletcher, Mark Stevenson

“…This study aimed to (1) create a dataset aggregating retraction information with bibliographic metadata, (2) train and evaluate various machine learning approaches to predict article retractions, and (3) assess each feature’s contribution to feature-based classifier performance using ablation studies. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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Development of novel hybrid models for the prediction of Covid-19 in Kuwait by Ahmad Aldousari, Maria Qurban, Ijaz Hussain, Maha Al-Hajeri

“…It is concluded that the proposed framework for the prediction of conformed corona cases indicated better performance as compared to other existing methods.  …”
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Advanced Machine Learning Techniques for Predicting Concrete Compressive Strength by Mohammad Saleh Nikoopayan Tak, Yanxiao Feng, Mohamed Mahgoub

“…The gradient boosting regressor (GBR) achieved the highest predictive accuracy with an R² value of 0.94. …”
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Indicator values for food shelf life prediction: A review by Teofilo Espinoza-Tellez, Roberto Quevedo-León, Oscar Diaz-Carrasco

“…This has motivated a progressive increase in studies that can determine the time at which the product can be safely consumed (shelf life). There are several methods for determining the shelf life of products; but regardless of the method used, the key is to know the minimum and/or maximum values of the indicators that define their deterioration. …”
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Application of continuum damage mechanics for prediction of wear in tillage tools by Sahar Ghatrehsamani, Mohammad Silani, Saleh Akbarzadeh, Shirin Ghatrehsamani

“…Many studies have primarily focused on experimental methods to better understand the impact of various parameters on tool wear during tilling operations. …”
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Relative importance of socioecological domains to predicting opioid-involved mortality. by Joshua C Black, Annika M Czizik

“…Community factors cumulatively had similar importance as individual drug-related factors in predicting opioid-involved deaths and were relatively more important in predicting opioid-involved mortality compared to non-drug involved mortality. …”
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Uncertainty-Aware Parking Prediction Using Bayesian Neural Networks by Alireza Nezhadettehad, Arkady Zaslavsky, Abdur Rakib, Seng W. Loke

“…Our approach leverages contextual features, including temporal and environmental factors, to enhance uncertainty-aware predictions. The framework is evaluated under varying data conditions, including data scarcity (90%, 50%, and 10% of training data) and synthetic noise injection to simulate aleatoric uncertainty. …”
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