From predictive analytics to emotional recognition–The evolving landscape of cognitive computing in animal welfare by Suresh Neethirajan

“…The discussion delves into various methodologies and algorithms that measure cognition, underscoring the pivotal role of cognitive computing in advancing animal welfare. …”
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Review on Sound-Based Industrial Predictive Maintenance: From Feature Engineering to Deep Learning by Tongzhou Ye, Tianhao Peng, Lidong Yang

“…Sound-based predictive maintenance (PdM) is a critical enabler for ensuring operational continuity and productivity in industrial systems. …”
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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

“…Deep learning (DL) technology has shown significant potential in the whole process of cataract diagnosis and treatment through algorithms such as convolutional neural network (CNN). …”
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A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…In this paper, we introduce a new search algorithm called Thermodynamic Inspired Search Algorithm (TSA) for approximate solution to linear ODEs (LODEs), nonlinear ODEs (NLODEs) and systems of ODEs (SODEs). …”
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Filter-Based Feature Selection Using Information Theory and Binary Cuckoo Optimisation Algorithm by Ali Muhammad Usman, Umi Kalsom Yusof, Maziani Sabudin

“…Dimensionality reduction is among the data mining process that is used to reduce the noise and complexity of features in various datasets. …”
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Exploring ethical frontiers of artificial intelligence in marketing by Harinder Hari, Arun Sharma, Sanjeev Verma, Rijul Chaturvedi

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Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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Energy prediction and optimization for robotic stereoscopic statue processing by Xu-Hui Cheng, Fang-Chen Yin, Cong-Wei Wen, Ye Wang, Yi-Hao Li, Ji-Xiang Huang, Shen-Gui Huang

“…Firstly, a prediction model for the robot’s body power is established by analyzing the energy consumption characteristics of the robot system. …”
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QSAR Models for Predicting the Antioxidant Potential of Chemical Substances by Sofia Ghironi, Edoardo Luca Viganò, Gianluca Selvestrel, Emilio Benfenati

“…Different machine learning algorithms were applied to build regression models, and the goodness-of-fit of each model was assessed using the statistical parameters of R squared (R²), the Root-Mean-Squared Error, and the Mean Absolute Error. …”
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Machine Learning‐Enabled Drug‐Induced Toxicity Prediction by Changsen Bai, Lianlian Wu, Ruijiang Li, Yang Cao, Song He, Xiaochen Bo

“…In this review, 10 categories of drug‐induced toxicity is examined, summarizing the characteristics and applicable ML models, including both predictive and interpretable algorithms, striking a balance between breadth and depth. …”
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Prediction of Global Ionospheric TEC Based on Deep Learning by Zhou Chen, Wenti Liao, Haimeng Li, Jinsong Wang, Xiaohua Deng, Sheng Hong

“…In this study, a prediction model of global IGS‐TEC maps are established based on testing several different long short‐term memory (LSTM) network (LSTM)‐based algorithms to explore a direction that can effectively alleviate the increasing error with prediction time. …”
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Unsupervised Action Anticipation Through Action Cluster Prediction by Jiuxu Chen, Nupur Thakur, Sachin Chhabra, Baoxin Li

“…Predicting near-future human actions in videos has become a focal point of research, driven by applications such as human-helping robotics, collaborative AI services, and surveillance video analysis. …”
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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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Comparing AI/ML approaches and classical regression for predictive modeling using large population health databases: Applications to COVID-19 case prediction by Lise M. Bjerre, Cayden Peixoto, Rawan Alkurd, Robert Talarico, Rami Abielmona

“…Objectives: This retrospective cohort study aimed to compare the predictive performance of AI/ML algorithms against conventional multivariate logistic regression models using linked health administrative data. …”
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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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MobNas ensembled model for breast cancer prediction by Tariq Shahzad, Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Iqbal, Ahmad Almogren, Yazeed Yasin Ghadi, Mamoon M. Saeed, Habib Hamam

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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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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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