Associations between anthropometric indices and biological age acceleration in American adults: insights from NHANES 2009–2018 data by Xinyun Chen, Xia Chen, Fangyu Shi, Wenhui Yu, Chang Gao, Shenju Gou, Ping Fu

“…Receiver Operating Characteristic (ROC) curve analysis assessed the predictive capabilities of the anthropometric indices. …”
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Assessment of sensor driven automatic smart soil and paddy seed metering mechanisms using artificial intelligence for paddy nurseries by Vinod Choudhary, Rajendra Machavaram, Prakhar Patidar, Gajendra Singh, Naseeb Singh, Lokesh Kumawat

“…The ANN-MOGA (multi-objective genetic algorithms) predicted higher experimental response values compared to the response surface methodology. …”
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Optimal channel multiplexing and maximal ratio combining: CINR comparison by V. P. Tuzlukov

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Method of Syntactic Analysis of Chinese Sentences on Topical Components by K. E. Kotcik

“…The article provides an overview of the methods of syntactic analysis of the constructions in the languages of the isolating type. The algorithms of the analysis of sentences of the Chinese language on topical components are proposed. …”
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Intelligent energy management of microgrids using machine learning: Leveraging random forest models for solar and wind power by Hasanur Zaman Anonto, Md Ismail Hossain, Abu Shufian, Md. Shaoran Sayem, S M Tanvir Hassan Shovon, Protik Parvez Sheikh, Sadman Shahriar Alam

“…The study at hand suggests dedicating a new type of energy management of the microgrid by using the machine-learning algorithms, namely the Random Forest (RF) regressor along with real-time forecasting the energy use and renewable-energy production. …”
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A Versatile, Machine-Learning-Enhanced RF Spectral Sensor for Developing a Trunk Hydration Monitoring System in Smart Agriculture by Oumaima Afif, Leonardo Franceschelli, Eleonora Iaccheri, Simone Trovarello, Alessandra Di Florio Di Renzo, Luigi Ragni, Alessandra Costanzo, Marco Tartagni

“…Thanks to the flexibility of the system’s architecture, which embeds a Linux operating system, we can easily embed machine learning (ML) algorithms and predictive models for information detection. …”
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AI-based classification of anticancer drugs reveals nucleolar condensation as a predictor of immunogenicity by Giulia Cerrato, Peng Liu, Liwei Zhao, Adriana Petrazzuolo, Juliette Humeau, Sophie Theresa Schmid, Mahmoud Abdellatif, Allan Sauvat, Guido Kroemer

“…Conclusions We developed AI-based algorithms for predicting CON-inducing drugs based on molecular descriptors and their validation using automated micrographs analysis, offering a new approach for screening ICD inducers with minimized adverse effects in cancer therapy.…”
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Big data and data science in global governance: anticipating future needs and applications in the UN and beyond by Lanxin Li, Jiarou Wang, Xi Wang, Peng Peng, Jiaying Shen, Haining Zhu, Ziyang Zhang

“…The research identifies the “4Vs” of big data (Volume, Velocity, Variety, and Veracity) as fundamental characteristics reshaping governance approaches while highlighting innovative applications like UN Global Pulse, SDG tracking systems, and AI-driven predictive analytics in crisis prevention. We assess technical, ethical, and organizational challenges, including data quality inconsistencies, interoperability issues, privacy concerns, algorithmic bias, and resource constraints that impede the full integration of big data into governance systems. …”
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Comprehensive evaluation of phosphoproteomic-based kinase activity inference by Sophia Müller-Dott, Eric J. Jaehnig, Khoi Pham Munchic, Wen Jiang, Tomer M. Yaron-Barir, Sara R. Savage, Martin Garrido-Rodriguez, Jared L. Johnson, Alessandro Lussana, Evangelia Petsalaki, Jonathan T. Lei, Aurelien Dugourd, Karsten Krug, Lewis C. Cantley, D. R. Mani, Bing Zhang, Julio Saez-Rodriguez

“…We used benchmarKIN to evaluate kinase-substrate libraries, inference algorithms and the potential of adding predicted kinase-substrate interactions to overcome the coverage limitations. …”
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Identifying potential biomarkers and molecular mechanisms related to arachidonic acid metabolism in vitiligo by Xiaoqing Li, Xiaoqing Li, Li Yang, Longfei Zhu, Jingying Sun, Jingying Sun, Cuixiang Xu, Cuixiang Xu, Lijun Sun, Lijun Sun

“…Machine-learning algorithms were used to identify six key genes as PTGDS, PNPLA8, FAAH, ABHD12, PTGS1, and MGLL. …”
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The diagnostic and prognostic capability of artificial intelligence in spinal cord injury: A systematic review by Saran Singh Gill, Hariharan Subbiah Ponniah, Sho Giersztein, Rishi Miriyala Anantharaj, Srikar Reddy Namireddy, Joshua Killilea, DanieleS.C. Ramsay, Ahmed Salih, Ahkash Thavarajasingam, Daniel Scurtu, Dragan Jankovic, Salvatore Russo, Andreas Kramer, Santhosh G. Thavarajasingam

“…Method: ology: The primary aim was to evaluate the performance of AI algorithms in diagnosing and prognosticating tSCI. Subsequent systematic searching of seven databases identified studies evaluating AI models. …”
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Impact of bridging the gap between Artificial Intelligence and nanomedicine in healthcare by Divyam Mishra, Bhavishya Chaturvedi, Vishal Soni, Dhairya Valecha, Megha Goel, Jamilur R. Ansari

“…We will also assess the long-term implications of lipid nanoparticles in drug delivery applications. Machine Learning algorithms are employed to create data-driven adaptive nanomaterials and paradigms, further advancing the field. …”
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Monitoring and modeling hydrologic conditions in Ukraine for hydropower generation by Matthew J. McCarthy, Jesus D. Gomez-Velez, David Hughes, Shannon Meade

“…To address this data gap, we developed a protocol that combined satellite-based time-series measurements of river width at seven locations throughout Ukraine from 2013 to 2023 with reanalysis data, climate-model predictions, and hydrologic models to both provide a means of monitoring a proxy for near-real-time discharge and also predict near-term (i.e., 2023–2030) hydrologic patterns for the region. …”
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Differences in parameter estimates derived from various methods for the ORYZA (v3) Model by Jun-wei TAN, Qing-yun DUAN, Wei GONG, Zhen-hua DI

“…The results showed that there were substantial differences between the parameter estimates derived by the different methods, and they had strong effects on model predictions. The parameter estimates given by the frequentist methods were obviously sensitive to initial values, and the extent of the sensitivity varied with algorithms and objective functions. …”
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Incorporating food plant distributions as important predictors in the habitat suitability model of sumatran orangutan (Pongo abelii) in Gunung Leuser National Park, Indonesia by Salmah Widyastuti, Wanda Kuswanda, M. Hadi Saputra, Hendra Helmanto, Nunu Anugrah, U. Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin

“…This study enhances habitat suitability models (HSM) for Sumatran orangutans by incorporating the predictive distributions for 21 key orangutan food plants, which had not been previously explored. …”
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A Machine Learning-Based Diagnostic Nomogram for Moyamoya Disease: The Validation of Hypoxia-Immune Gene Signatures by Cunxin Tan, Xilong Wang, Zhenyu Zhou, Yutong Liu, Shihao He, Yuanli Zhao

“…These genes were further refined through machine learning algorithms. The diagnostic value was confirmed using an external dataset, and a diagnostic nomogram was constructed. …”
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Trends in management of odontoid fractures 2010–2021 by Michael J. Gouzoulis, BS, Anthony E. Seddio, BS, Albert Rancu, BS, Sahir S. Jabbouri, MD, Jay Moran, MD, Arya Varthi, MD, Daniel R. Rubio, MD, Jonathan N. Grauer, MD

“…While these decisions were predicted by some clinical factors, both also correlated with nonclinical factors suggesting room for more consistent algorithms.…”
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Diagnosing prostate cancer in the PSA gray zone through machine learning and transrectal ultrasound video by Qin Wu, Chengyi Wu, Maoliang Zhang, Jie Yang, Junxiang Zhang, Yun Jin, Yanhong Du, Xingbo Sun, Liyuan Jin1, Kai Wang, Zhengbiao Hu, Xiaoyang Qi1, Jincao Yao, Zhengping Wang, Dong Xu

“…Background: We developed a machine learning-based predictive model for diagnosing prostate cancer within the gray zone of prostate-specific antigen (PSA) levels, leveraging transrectal prostate ultrasound video clips. …”
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The National Police in the system of administrative delinquency prevention subjects by O. M. Muzychuk

“…Measurement and analysis of this indicator are rather complex processes, as they are carried out not only within the framework of police activities, but are also largely related to the functioning of civil society institutions, educative, cultural, scientific and educational institutions and organisations, including international ones, which focus their activities on solving urgent problems that constitute the social basis of administrative delinquency. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Despite these advancements, challenges remain, particularly concerning data privacy, security, and algorithmic bias. Ensuring robust data governance and ethical practices is crucial for the continued success of AI integration in ophthalmology. …”
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