MOF-MoS2 nanosheets doped PEDOT:PSS for organic electrochemical transistors in enhanced glucose sensing and machine learning-based concentration prediction by Yali Sun, Yun Li, Yang Zhou, Ting Cai, Yuxuan Chen, Chao Zou, Han Song, Shenghuang Lin, Shenghua Liu

“…Finally, we illustrate the merits of integration machine learning algorithms to construct predictive models using the extensive datasets produced by our sensors for both classification and quantification tasks. …”
Get full text

Explainable artificial intelligence for sustainable urban water systems engineering by Shofia Saghya Infant, Sundaram Vickram, A Saravanan, C M Mathan Muthu, Devarajan Yuarajan

“…This highlights the promise of XAI as a tool to improve sustainable practices in water management by providing a link between highly complex algorithms and watertight management decisions that are easier to implement.…”
Get full text

The future of AI in government services and global risks: insights from design fictions by Pedro Vitor Marques Nascimento, Paloma Beatriz Belchior de Siqueira, Nathalia Chrispim, Ramon Miranda Chaves, Carlos Eduardo Barbosa, Jano Moreira de Souza

“…The findings highlight three critical dilemmas: (1) AI’s dual role in enhancing efficiency while exacerbating algorithmic bias and surveillance concerns; (2) the potential displacement of human roles in public services, raising questions about accountability and transparency; and (3) the ethical trade-offs in AI-driven decision-making, particularly in law enforcement, healthcare, and education. …”
Get full text

Detecting Changes in Soil Fertility Properties Using Multispectral UAV Images and Machine Learning in Central Peru by Lucia Enriquez, Kevin Ortega, Dennis Ccopi, Claudia Rios, Julio Urquizo, Solanch Patricio, Lidiana Alejandro, Manuel Oliva-Cruz, Elgar Barboza, Samuel Pizarro

“…A UAV-captured image was used to predict the spatial distribution of soil parameters, generating fourteen spectral indices and a digital surface model (DSM) from 103 soil plots across 49.83 hectares. Machine learning algorithms, including classification and regression trees (CART) and random forest (RF), modeled the soil parameters (N-ppm, P-ppm, K-ppm, OM%, and EC-mS/m). …”
Get full text

ProgModule: A novel computational framework to identify mutation driver modules for predicting cancer prognosis and immunotherapy response by Xiangmei Li, Bingyue Pan, Xilong Zhao, Yinchun Su, Jiyin Lai, Siyuan Li, Yalan He, Jiashuo Wu, Junwei Han

“…Abstract Background Cancer originates from dysregulated cell proliferation driven by driver gene mutations. Despite numerous algorithms developed to identify genomic mutational signatures, they often suffer from high computational complexity and limited clinical applicability. …”
Get full text

Enhancing SAR-ATR Systems’ Resistance to S2M Attacks via FUA: Optimizing Surrogate Models for Adversarial Example Transferability by Xiaying Jin, Shuangju Zhou, Chenyu Wang, Mingxin Fu, Quan Pan, Yang Li

“…Experimental results demonstrate that FUA can outperform SOTA methods and significantly improve the S2M transferability across various adversarial attack algorithms. The optimization strategies at each phase can contribute to overall performance improvements.…”
Get full text

Artificial Neural Network for Air Pollutant Concentration Predictions Based on Aircraft Trajectories over Suvarnabhumi International Airport by Patcharin Kamsing, Chunxiang Cao, Wuttichai Boonpook, Sornkitja Boonprong, Min Xu, Pisit Boonsrimuang

“…By leveraging Automatic Dependent Surveillance-Broadcast (ADS-B) historical data, aircraft trajectory pattern clustering is implemented by using K-means and Gaussian mixture model (GMM) clustering algorithms. Then, those trajectory patterns are inputted together with other flight data into ANN computation processes, resulting in an effective air pollutant prediction model for each kind of focus pollutant. …”
Get full text

Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment by Mohammad Saleem, Abigail E. Watson, Aisha Anwaar, Ahmad Omar Jasser, Nabiha Yusuf

“…A machine learning-based approach was able to assess the risk-benefit ratio for the prediction of immune-related adverse events (irAEs) using the electronic health record (EHR) data. Deep learning algorithms demonstrated high accuracy in tumor microenvironment analysis, including tumor region identification and lymphocyte detection. …”
Get full text

A Comprehensive Review on Lithium-Ion Battery Lifetime Prediction and Aging Mechanism Analysis by Seyed Saeed Madani, Yasmin Shabeer, François Allard, Michael Fowler, Carlos Ziebert, Zuolu Wang, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou, Khay See, Kaveh Khalilpour

“…It introduces emerging strategies that leverage advanced algorithms to improve predictive model precision, ultimately driving enhancements in battery performance and supporting their integration into various systems, from electric vehicles to renewable energy infrastructures.…”
Get full text

Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…The optical time domain reflectometer (OTDR) curve features of communication fibers exhibit subtle differences among their normal, subhealthy, and faulty operating states, making it challenging for existing machine learning-based fault diagnosis algorithms to extract these minute features. In addition, the OTDR curve field fault data are scarce, and data-driven deep neural network that needs a lot of data training cannot meet the requirements. …”
Get full text

Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning by Wenhui Chen, Wenhui Chen, Wenhui Chen, Qingling Yang, Qingling Yang, Qingling Yang, Linli Hu, Linli Hu, Linli Hu, Mengchen Wang, Mengchen Wang, Mengchen Wang, Ziyao Yang, Ziyao Yang, Ziyao Yang, Xinxin Zeng, Xinxin Zeng, Xinxin Zeng, Yingpu Sun, Yingpu Sun, Yingpu Sun

“…By analyzing differentially expressed genes (DEGs) and module genes using weighted gene co-expression networks (WGCNA), functional enrichment analysis, and three machine learning algorithms, we identified twelve diseases shared genes, and two diagnostic genes, including GLIPR1 and MAMLD1. …”
Get full text

GUIDELINES ON ARTERIAL HYPERTENSION MANAGEMENT OF THE EUROPEAN SOCIETY OF CARDIOLOGY AND EUROPEAN SOCIETY OF HYPERTENSION 2018: WHAT’S NEW? by A. A. Klimenko, D. A. Anichkov, N. A. Demidova

“…The latest guidelines contain simplified algorithms for management of patients with AH. It is shown that in most patients, a preference should be made for combinations of renin-angiotensin-aldosterone system blocker (inhibitors of angiotensin-converting enzyme or angiotensin II receptor blockers) with a slow calcium channels blocker and/or thiazide/thiazide-like diuretic. …”
Get full text

A Robust Framework for Bamboo Forest AGB Estimation by Integrating Geostatistical Prediction and Ensemble Learning by Lianjin Fu, Qingtai Shu, Cuifen Xia, Zeyu Li, Hailing He, Zhengying Li, Shaoyang Ma, Chaoguan Qin, Rong Wei, Qin Xiang, Xiao Zhang, Yiran Zhang, Huashi Cai

“…Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. …”
Get full text

Persistent vegetation greening trends across China’s wetlands by Yongxing Ren, Dehua Mao, Tao Wang, Mohamed Abdalla, Pete Smith, Xiangming Xiao, Zicheng Yu, Xiuxue Chen, Yanbiao Xi, Ling Luo, Xiaoyan Li, Zongming Wang

“…Based on this dataset, we mapped the spatial distribution of wetland AGB in China using machine learning algorithms to understand its historical and future changes. …”
Get full text

Development and Validation of Survival Prediction Models for Patients With Pineoblastomas Using Deep Learning: A SEER‐Based Study by Xuanzi Li, Shuai Yang, Yingpeng Peng, Xueqiang You, Shunli Peng, Siyang Wang, Dasong Zha, Shuyuan Zhang, Chuntao Deng

“…These results indicate the potential of DL algorithms to improve outcome prediction in patients with rare tumors.…”
Get full text

Cultivating clean skies: unveiling the tapestry of air quality in Gujarat through innovative machine learning analysis by Gaddam Advitha, Allada Nagasai Varaprasad, Koti Vennela Khushi, Pullabhotla Vijay, Sukanta Nayak

“…This research delves into the utilization of Machine Learning (ML) algorithms, specifically Random Forest (RF) and XGBoost, to predict AQIs in Gujarat. …”
Get full text

Comparative Study on EDM Wire Cutting and CO2 Laser Cutting for High‐Precision Stainless Steel Sheet Processing by A. Parthiban, K. Ananthakumar, S. Ajith Arul Daniel, S. Sivaganesan, T. Sathish, Jayant Giri, A. Johnson Santhosh, Ahmad O. Hourani

“…Using a multi‐objective optimization approach based on Genetic Algorithms, the study demonstrates a significant enhancement in surface roughness. …”
Get full text

Expose flexible conformations for intrinsically disordered protein by Jiaan Yang, Wenxin Ji, Wen Xiang Cheng, Gang Wu, Si Tong Sheng, Peng Zhang, Jun Lin, Xiaojia Chen, Qiong Shi

“…To overcome the barrier, the protein structure fingerprint technology has been developed, which includes PFSC (Protein Folding Shape Code) (Yang, 2008) and PFVM (Protein Folding Variation Matrix) (Yang et al., 2022) algorithms as well as FiveFold (Yang et al., 2025) approach for protein structure prediction, which are able explicitly to expose the possible conformational structures for intrinsically disordered protein. …”
Get full text

Ensemble Learning-Driven and UAV Multispectral Analysis for Estimating the Leaf Nitrogen Content in Winter Wheat by Yu Han, Jiaxue Zhang, Yan Bai, Zihao Liang, Xinhui Guo, Yu Zhao, Meichen Feng, Lujie Xiao, Xiaoyan Song, Meijun Zhang, Wude Yang, Guangxin Li, Sha Yang, Xingxing Qiao, Chao Wang

“…Support Vector Regression (SVR), Random Forest (RF), Ridge Regression (RR), K-Nearest Neighbors (K-NN), and ensemble learning algorithms (Voting and Stacking) were employed to model the relationship between selected vegetation indices and LNC. …”
Get full text

Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…Secondly, research efforts are concentrated within limited institutions, focusing on certain research questions, algorithms, raw materials, and use-wear traces. Thirdly, the inadequate quality, quantity, and diversity of data affect the performance of the models being developed. …”
Get full text