Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997–2014) by Elma Dervić, Katharina Ledebur, Stefan Thurner, Peter Klimek

“…The dataset provides the possibility to researchers to create their own, tailor-made comorbidity networks from real patient data that can be used as a starting point in quantitative and machine learning methods. This data platform is intended to lead to deeper insights into a wide range of epidemiological, public health, and biomedical research questions.…”
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Directed Energy Deposition via Artificial Intelligence-Enabled Approaches by Utkarsh Chadha, Senthil Kumaran Selvaraj, Aakrit Sharma Lamsal, Yashwanth Maddini, Abhishek Krishna Ravinuthala, Bhawana Choudhary, Anirudh Mishra, Deepesh Padala, Shashank M, Vedang Lahoti, Addisalem Adefris, Dhanalakshmi S

“…Moreover, artificial intelligence and machine learning implementation has increased for further applications and advancements. …”
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Data analysis-based framework for the design and assessment of chemical process plants: a case study in amine gas-treating systems by Rahul Gupta, Gladys Navas, Daniela Galatro

“…This work presents a process-integrity assessment framework to chemical process design that combines first principles, heuristics, vendor specifications, standards/codes, data analysis, and machine learning modelling, hypothesized as an efficient route for optimal process design. …”
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Nabeel Saleem Saad Al-Bdairi

“…This paper proposes a novel hybrid machine learning model based on an artificial neural network (ANN) and the Marine Predators algorithm (MPA) for modeling monthly water levels of the Tigris River in Al-Kut, Iraq. …”
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Effective Processing of Radar Data for Bridge Damage Detection by Tomasz Owerko, Przemysław Kuras

“…In addition, the distribution of errors and the sensitivity of classifiers based on the DSF parameter and Cook’s distances leaving them will enable the automation of the classification process using machine learning. The proposed method is universal; in particular, it can be used for radar interferometry methods because it is resistant to potentially variable environmental conditions.…”
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Content-Based Image Retrieval Using Colour, Gray, Advanced Texture, Shape Features, and Random Forest Classifier with Optimized Particle Swarm Optimization by Manoharan Subramanian, Velmurugan Lingamuthu, Chandran Venkatesan, Sasikumar Perumal

“…The matching accuracy and the speed of image retrieval are improved by an ensemble of machine learning algorithms for the similarity search.…”
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Similarity-Based Summarization of Music Files for Support Vector Machines by Jan Jakubik, Halina Kwaśnicka

“…These results suggest that adjusting deep learning methods to build data representations that target a specific classifier or regressor can open up new perspectives for the use of standard machine learning methods in music domain.…”
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Random Forest–Based Coal Mine Roof Displacement Prediction and Application by Hongxia Li, Rong Wu, Jianan Gao

“…Therefore, this study puts forward the machine learning method to study the advance prediction of coal roadway roof displacement. …”
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Improving Diabetic Patients Monitoring System Using (NCA-CNN) Algorithm based on loT by Ayas Talib Mohammad, Jaber Parchami

“… The Internet of Things (IoT) and Artificial Intelligence (AI), particularly Machine Learning (ML), have both seen significant advancements in recent years, which has resulted in significant leaps forward in the development of health monitoring systems. …”
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Inteligencia artificial y derechos humanos by Juan Esteban Yanguas Ramón, Isabella Narváez Peña

“…El artículo explora, desde la teoría, diversos conceptos, pasando por el machine learning y la analítica de datos, así como los derechos humanos desde definiciones informales hasta formales, analizando sus elementos y los sistemas de protección de estos derechos. …”
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Evaluation of Different Stemming Techniques on Arabic Customer Reviews by Hawraa Fadhil Khelil, Mohammed Fadhil Ibrahim, Hafsa Ataallah Hussein, Raed Kamil Naser

“…This work sheds light on utilizing and investigating more machine learning (ML) techniques and evaluating the results.  …”
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A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture by Halil Karahan, Müge Erkan Can

“…The proposed model, although based on an artificial neural network (ANN), also has the potential to be adapted for methods used in machine learning and artificial intelligence, such as Support Vector Machines, Decision Trees, Random Forests, and Ensemble Learning Methods.…”
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Leveraging multiplexed metasurfaces for multi-task learning with all-optical diffractive processors by Behroozinia Sahar, Gu Qing

“…Diffractive Neural Networks (DNNs) leverage the power of light to enhance computational performance in machine learning, offering a pathway to high-speed, low-energy, and large-scale neural information processing. …”
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Knowledge Graph Analysis of Digital Emergency Management Research Based on CiteSpace Visualisation: Comparative Analysis of WOS and CNKI Databases by Rui Nan, Wenjun Zhu, Yejing Xiao

“…The former are information technology, artificial intelligence, and machine learning, whereas the latter are emergency decision making, scenario analysis, and public health.…”
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Forecasting of Ionospheric Total Electron Content Data Using Multivariate Deep LSTM Model for Different Latitudes and Solar Activity by Nayana Shenvi, Hassanali Virani

“…The performance of the LSTM model was validated by comparing it with the multilayer perceptron (MLP) machine learning algorithm using root mean square error (RMSE) and mean absolute error (MAE) as evaluation indices. …”
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Interpreting convolutional neural networks' low-dimensional approximation to quantum spin systems by Yilong Ju, Shah Saad Alam, Jonathan Minoff, Fabio Anselmi, Han Pu, Ankit Patel

“…In this work, we use methodologies from information theory, group theory and machine learning, to elucidate how CNN captures relevant physics of quantum systems. …”
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Unlocking autism’s complexity: the Move Initiative’s path to comprehensive motor function analysis by Ashley Priscilla Good, Elizabeth Horn

“…Despite advances in sensors, wearables, algorithms, machine learning, and agentic AI, autism research remains siloed, with many tools inaccessible to affected families and care teams. …”
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Efficient anomaly detection in tabular cybersecurity data using large language models by Xiaoyong Zhao, Xingxin Leng, Lei Wang, Ningning Wang, Yanqiong Liu

“…While traditional machine learning and deep learning methods have shown some success, they continue to face significant challenges in terms of generalization. …”
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Ontology-based prompt tuning for news article summarization by A. R. S. Silva, Y. H. P. P. Priyadarshana

“…Despite the progress in natural language processing (NLP) and machine learning, existing methods often rely on extractive summarization, which lacks the ability to generate coherent and contextually rich summaries. …”
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Hierarchical Aggregation for Federated Learning in Heterogeneous IoT Scenarios: Enhancing Privacy and Communication Efficiency by Chen Qiu, Ziang Wu, Haoda Wang, Qinglin Yang, Yu Wang, Chunhua Su

“…Federated Learning (FL) is a distributed machine-learning paradigm that enables models to be trained across multiple decentralized devices or servers holding local data without transferring the raw data to a central location. …”
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