Investigating the hydrogen renaissance in the global energy transition with AI integration by Abderrahim Lakhouit

“…In storage, AI-driven algorithms are improving the management of hydrogen in large-scale storage systems, helping to mitigate issues such as leakage and optimizing storage conditions. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…Interestingly, while the more complex optimization models yield better overall welfare results, the improvements over simpler methods are small. …”
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PSO Tuned Super-Twisting Sliding Mode Controller for Trajectory Tracking Control of an Articulated Robot by Zewdalem Abebaw Ayinalem, Abrham Tadesse Kassie

“…This paper introduces a novel method that integrates SolidWorks modeling to create precise digital representations of the robot’s mechanical structure, facilitating easier development and simulation of control algorithms. …”
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Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…The proposed coordination algorithms make it possible to optimize the operating modes of the system automatically when its structure and/or settings are changed. …”
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Reinforcement learning applications in water resource management: a systematic literature review by Linus Kåge, Vlatko Milić, Vlatko Milić, Maria Andersson, Magnus Wallén

“…Reinforcement learning (RL) has demonstrated promising potential in optimization and planning tasks, as it trains models on historical data or through simulations, allowing them to generate new data by interacting with the simulator. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…Furthermore, ethical considerations such as data privacy, algorithmic bias, and equitable access are crucial to ensuring that AI-driven solutions are implemented responsibly and inclusively.This review also explores future directions for AI, including the development of sophisticated predictive models, autonomous systems for high-risk tasks, immersive training programs utilizing virtual and augmented reality, and global collaboration aimed at standardizing AI tools and practices. …”
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Natural language processing for enhanced feedback mechanisms in breast cancer care: a systematic review and comparative exploration by Faezeh Firuzpour, Hamid Reza Saeidnia

“…Through a structured review of 28 relevant studies, we identified key advancements in NLP algorithms for analyzing patient feedback, including their integration with social media, online forums, and Electronic Health Records (EHRs). …”
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More than a chatbot: a practical framework to harness artificial intelligence across key components to boost digital therapeutics quality by Amit Baumel

“…The rapid advancement of Artificial Intelligence (AI)-powered large language models has highlighted the potential of AI-based chatbots to create a new era for digital therapeutics (DTx)—digital behavioral and mental health interventions. …”
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Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques by Obsa Gelchu Horsa, Kula Kekeba Tune

“…The implementation result shows that the optimal values of models’ performance evaluation parameters were generated using different hyperparameter tuning settings.…”
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Economic burden of the novel coronavirus infection: a systematic review by V. M. Timiryanova, I. A. Lakman, N. Sh. Zagidullin, D. F. Gareeva

“…Predominantly, the estimates involve the calculation of quality-adjusted life years lost (QALY) (66.3%), 37.6% of the studies are based on the results of constructing scenario models, 28.8% consume algorithms of epidemiological SIR (susceptible, infected, or recovered) models, and 66.3% provide for cost assessment. …”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…It highlights state-of-the-art AI techniques and synthesizes insights into their potential to improve diagnostic outcomes. Additionally, the analysis underscores common challenges, including dataset limitations, variability in preprocessing approaches, and the need for more interpretable models. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…This approach enhances the flexibility of algorithms by incorporating diverse data. A growing quantity of current research has focused on the exploration of extracting data from multiple sources and constructing precise multimodal machine/deep learning models for medical examinations. …”
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Identifying potential three key targets gene for septic shock in children using bioinformatics and machine learning methods by Wei Guo, Hao Chen, Feng Wang, Yingjiao Chi, Wei Zhang, Shan Wang, Kezhu Chen, Hong Chen

“…Three kinds of machine learning models were established, and the candidate genes were screened by intersection to obtain the core genes with diagnostic value. …”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. …”
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The Comparison of Classical Statistical and Machine Learning Methods in Prediction of Thrombosis in Patients with Acute Myeloid Leukemia by Ilija Doknić, Mirjana Mitrović, Zoran Bukumirić, Marijana Virijević, Nikola Pantić, Nikica Sabljić, Darko Antić, Živko Bojović

“…Multilayer Perceptron (MLP) was found to be the best fit among the models evaluated, achieving the C statistic of 0.749. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…Deep learning-based models assist radiologists by detecting patterns, generating probability maps, and predicting outcomes like heart failure. …”
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Transforming heart transplantation care with multi-omics insights by Zhengbang Zou, Jianing Han, Zhiyuan Zhu, Shanshan Zheng, Xinhe Xu, Sheng Liu

“…Single–cell omics technologies and machine learning algorithms further resolve cellular heterogeneity and improve predictive modeling, thereby enhancing the clinical translatability of multi-omics data. …”
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Can We Teach Machines to Select Like a Plant Breeder? A Recommender System Approach to Support Early Generation Selection Decisions Based on Breeders’ Preferences by Sebastian Michel, Franziska Löschenberger, Christian Ametz, Herbert Bistrich, Hermann Bürstmayr

“…Plant breeding is considered to be the science and art of genetically improving plants according to human needs. Breeders in this context oftentimes face the difficult task of selecting among thousands of genotypes for dozens of traits simultaneously. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Combined models for multiple varieties from field test samples achieved classification accuracies of 0.731. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…AI-driven technologies, including deep learning algorithms and machine learning models, are emerging as valuable tools in cervical cancer detection, risk assessment, and treatment planning. …”
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