Construction and Comprehensive Prognostic Analysis of a Novel Immune-Related lncRNA Signature and Immune Landscape in Gastric Cancer by Xiaolong Liang, Lang Zha, Gangfeng Yu, Xiong Guo, Chuan Qin, Anqi Cheng, Ziwei Wang

“…Therefore, effective predictive biomarkers are urgently needed for GC patients to realize the benefits of immunotherapy. …”
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Extending the forecasting horizon of daily new COVID-19 cases using non-pharmaceutical measures and the effective reproduction number (Rt): A deep learning-based framework by Tuga Mauritsius

“…The inclusion of additional variables was found to diminish the predictive accuracy of DL algorithms.…”
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Unbalance Responses of Rotor/Stator Systems with Nonlinear Bearings by the Time Finite Element Method by D. Demailly, F. Thouverez, L. Jézéquel

“…The current trend is to take into account many kinds of non-linearities in order to obtain more realistic predictions. The use of algorithms based on nonlinear methods is therefore needed. …”
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Construction of the miRNA/Pyroptosis-Related Molecular Regulatory Axis in Abdominal Aortic Aneurysm: Evidence From Transcriptome Data Combined With Multiple Machine Learning Approa... by Yongchao Su, Chuangang Lu, Shuchen Chen

“…Conclusion: A predictive model (PRG classifier) incorporating eight PRGs through multiple machine learning algorithms was developed and validated. …”
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AI-driven healthcare: Fairness in AI healthcare: A survey. by Sribala Vidyadhari Chinta, Zichong Wang, Avash Palikhe, Xingyu Zhang, Ayesha Kashif, Monique Antoinette Smith, Jun Liu, Wenbin Zhang

“…We emphasize the necessity of diverse datasets, fairness-aware algorithms, and regulatory frameworks to ensure equitable healthcare delivery. …”
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The Effect of Derived Features on Art Genre Classification with Machine Learning by Didem Abidin

“…Although this process was used to be done by art experts before, now artificial intelligence techniques may help people manage this classification task. The algorithms used for classification are already improved, and now they can make classifications and predictions for any kind of genre classification. …”
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Digital Methods to Study (and Reduce) the Impact of Disinformation by Miriam Di Lisio, Domenico Trezza

“…The second is that algorithms could be sources of bias. Social media companies need to be very careful about relying on automated classification. …”
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Machine Learning Modeling of Disease Treatment Default: A Comparative Analysis of Classification Models by Michael Owusu-Adjei, James Ben Hayfron-Acquah, Frimpong Twum, Gaddafi Abdul-Salaam

“…The focus on contextual nonbiomedical measurements using a supervised machine learning modeling technique is aimed at creating an understanding of the reasons why treatment default occurs, including identifying important contextual parameters that contribute to treatment default. The predicted accuracy scores of four supervised machine learning algorithms, namely, gradient boosting, logistic regression, random forest, and support vector machine were 0.87, 0.90, 0.81, and 0.77, respectively. …”
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Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD). by Yang S Liu, Fernanda Talarico, Dan Metes, Yipeng Song, Mengzhe Wang, Lawrence Kiyang, Dori Wearmouth, Shelly Vik, Yifeng Wei, Yanbo Zhang, Jake Hayward, Ghalib Ahmed, Ashley Gaskin, Russell Greiner, Andrew Greenshaw, Alex Alexander, Magdalena Janus, Bo Cao

“…Key predictive factors included EDI subdomain scores, sex, and socioeconomic status. …”
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Combining CFD and AI/ML Modeling to Improve the Performance of Polypropylene Fluidized Bed Reactors by Nayef Ghasem

“…It also combines CFD with artificial intelligence and machine learning (AI/ML) algorithms, like artificial neural networks (ANN), resulting in a powerful predictive tool for accurately predicting reactor metrics based on operating conditions. …”
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Optimising 3D-printed carbon fibre composites using machine learning: Balancing strength and efficiency by José Humberto S. Almeida, Jr., Guilherme Ferreira Gomes

“…This study introduces a data-driven framework that integrates machine learning (ML) and genetic algorithms (GA) to optimise interlaminar strength and minimise printing time simultaneously. …”
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Exploring Protein Conformational Changes Using a Large‐Scale Biophysical Sampling Augmented Deep Learning Strategy by Yao Hu, Hao Yang, Mingwei Li, Zhicheng Zhong, Yongqi Zhou, Fang Bai, Qian Wang

“…Abstract Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. …”
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NMR-based metabolomic approach to estimate chemical and sensorial profiles of olive oil by Gaia Meoni, Leonardo Tenori, Francesca Di Cesare, Stefano Brizzolara, Pietro Tonutti, Chiara Cherubini, Laura Mazzanti, Claudio Luchinat

“…By integrating NMR data with traditional chemical analyses and sensory evaluation, we developed multivariate models to evaluate the predictive power of NMR spectra coupled with machine learning algorithms for 50 distinct olive oil quality parameters, including physicochemical properties, fatty acid composition, total polyphenols, tocopherols, and sensory attributes. …”
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Role of artificial intelligence in medical radiology and imaging by Mohd Arfat, T. K. Nisha, Sapna Sahu, Mohd Rashid

“…AI is crucial in analyzing large medical datasets, including imaging and clinical data, through advanced algorithms and ML techniques. In veterinary medicine, AI is key to addressing complex challenges in host–pathogen interactions, precision medicine, and predictive epidemiology. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Bayesian causal discovery provides a principled framework for modeling observational data, generating posterior distributions that best represent the underlying structure. While recent algorithms offer efficient and accurate structure learning, integrating experiment design can further enhance predictive performance. …”
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The Future of Economic Modelling by A.O. Moscardini, K. Lawler, T. Vlasova, E. Merza

“…Traditional Economic modelling is still a useful tool for understanding and teaching but Data Analytics and intelligent algorithms are better for economic predictions.…”
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Applications of artificial intelligence and computational intelligence in hydraulic optimization of centrifugal pumps: a comprehensive review by Yuanhui Xu, Xingcheng Gan, Ji Pei, Wenjie Wang, Jia Chen, Shouqi Yuan

“…Ultimately, such progress will contribute to more sustainable and reliable energy utilisation in diverse industrial applications.Highlights Comprehensive review of AI and CI applications in centrifugal pump hydraulic optimisation.Analysis of machine learning methods for predictive modelling and optimisation.Insights into integrating intelligent algorithms with CFD for high-dimensional, multi-objective optimisation.Identification of future research directions to enhance precision and efficiency in pump design methodologies.…”
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Index or illusion: The case of frailty indices in the Health and Retirement Study. by Yi-Sheng Chao, Hsing-Chien Wu, Chao-Jung Wu, Wei-Chih Chen

“…The input variables better predicted mortality than the FIs. The continuous FIs predicted mortality better than the frailty statuses. …”
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Global research trends in AI-assisted blood glucose management: a bibliometric study by Li Yuan, Li Yuan, Yangtian Wang, Meiping Xing, Tao Liu, Dan Xiang

“…Major research clusters included CGM, machine learning algorithms, and predictive modeling. The United States, Italy, and the UK were prominent contributors, with key journals such as Diabetes Technology & Therapeutics leading the field.ConclusionAI technologies are significantly advancing blood glucose management, especially through machine learning and predictive models. …”
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An Intelligent System for Medical Oxygen Consumption Management Using Oximetry and Barometry by Abbas Izadi, Hadi Ghasemifard, Mohamad Amin Bakhshali, Nadia Roudsarabi, Omid Sarrafzadeh

“…The system integrates various sensors and machine learning algorithms to enable real-time monitoring and control of the oxygen supply chain. …”
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