Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory by Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore

“…Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The subtle changes in hearing often go unnoticed, presenting a challenge for early hearing loss detection. While machine learning shows promise, prior studies have not leveraged cardiovascular risk factors known to impact hearing. …”
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Higher-order aberrations and spherical aberration in various age groups after LASIK and cataract surgery by Robert Edward T. Ang, Patricia L. Lee, Ryan S. Torres, Michelle Marie Q. Araneta, Emerson M. Cruz, Maria Socorro M. Torno

“…In Lasik surgery, manipulating spherical aberration in the corneal periphery improves overall vision while in the central cornea provides presbyopic treatment. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…The Datalist system ensures seamless transitions between analytical workflows, while the “savepoints” feature enhances reproducibility by preserving the analysis state. …”
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Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics by Tian Zhang, Ying Deng, Wentao Wang, Zhe Zhao, Yiling Wu, Haoqian Wang, Shutao Xia, Weifang Liao, Weijie Liao

“…Abstract The prompt diagnosis of pulmonary infections with unknown etiology in patients in severe condition remains a challenge due to the lack of rapid and effective diagnostic methods. While metatranscriptomic sequencing offers a powerful approach, its clinical utility is often limited by issues of timeliness. …”
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Exploring the key ingredients and mechanisms of Banxia Xiexin decoction for the treatment of polycystic ovary syndrome based on network pharmacology and experimental validation by Bai Hai, Yingying Zhang, Jing Huang, Richard Mprah, Mingming Wang

“…KEGG analysis showed they were mainly involved in signaling pathways such as PI3K-AKT, MAPK, HIF-1 and IL17. By PPI and algorithmic analysis, we identified 8 hub genes, 5 of which (JUN, MAPK1, MAPK3, FOS, TP53) were related to oxidative stress. …”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…High PCDS correlated with upregulated pathways related to inflammation and immune response, while low PCDS associated with protective pathways. …”
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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…The results showed that the majority of students (59.2 %) positively assess the use of neural networks, while 85.1 % of respondents use them for educational purposes. …”
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Quantifying the Accuracy of UAS-Lidar Individual Tree Detection Methods Across Height and Diameter at Breast Height Sizes in Complex Temperate Forests by Benjamin T. Fraser, Russell G. Congalton, Mark J. Ducey

“…This study addresses how specific individual tree detection (ITD) methods impact the successful detection of trees of varying sizes within complex forests. First, while many studies have compared ITD methods over several sites, algorithms, or sets of parameters based on a singular validation metric, this study quantifies how 10 processing methods perform across varying tree-height size quartiles and varying tree diameter at breast height (dbh) size quartiles. …”
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Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data by Alireza Farnoush, Zahra Sedighi-Maman, Behnam Rasoolian, Jonathan J. Heath, Banafsheh Fallah

“…Abstract The presence of adverse drug reactions (ADRs) is an ongoing public health concern. While traditional methods to discover ADRs are very costly and limited, it is prudent to predict ADRs through non-invasive methods such as machine learning based on existing data. …”
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Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG by Yavuz Selim Kıyak, Andrzej A Kononowicz

“… Abstract BackgroundTemplate-based automatic item generation (AIG) is more efficient than traditional item writing but it still heavily relies on expert effort in model development. While nontemplate-based AIG, leveraging artificial intelligence (AI), offers efficiency, it faces accuracy challenges. …”
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Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorectal cancer by Tianle Xue, Yunpeng Chen, Xiaomeng Li, Zhixiang Zhou, Qiyang Chen

“…An integrated machine learning (IML) model—utilizing 12 algorithms with 10-fold cross-validation—was constructed to pinpoint key diagnostic biomarkers. …”
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Multi-crop plant counting and geolocation using a YOLO-Powered GUI System by Renato Herrig Furlanetto, Nathan Schawn Boyd, Ana Claudia Buzanini

“…Crop counting has traditionally relied on manual field assessments or complex machine learning algorithms, which often struggle to identify small objects or underestimate the total count of objects present in the field. …”
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An interpretable electrocardiogram-based model for predicting arrhythmia and ischemia in cardiovascular disease by Tanjila Alam Sathi, Rafsan Jany, Razia Zaman Ela, AKM Azad, Salem Ali Alyami, Md Azam Hossain, Iqram Hussain

“…Ischemia, due to reduced myocardial blood flow, can lead to sudden cardiac death, while arrhythmias, marked by abnormal heart rhythms, are common in the elderly. …”
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Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…(CRC: n = 150, Healthy: n = 127) were subjected to three machine learning algorithms, eXtreme gradient boosting (XGBoost), Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO). …”
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Using correlative science, open access big data and ensemble machine learning to track contamination signals in the wild: A first landscape-scale prediction for the Himalayan vultu... by Dikpal Krishna Karmacharya, Ganesh Puri, Ganga Ram Regmi, Madan Krishna Suwal, Falk Huettmann

“…We used latest machine learning algorithms to obtain the best possible prediction for inference. …”
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Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications by Peiqingfeng Wang, Shusheng Xu, Xuerong Shi, Jiaqing Zhu, Haichao Xiong, Huimin Wen

“…Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…In this manuscript, an Underwater Object Detection and Classification Utilizing the Ensemble Deep Learning Approach and Hybrid Optimization Algorithms (UODC-EDLHOA) technique is developed. The UODC-EDLHOA technique mainly detects and classifies underwater objects using advanced DL and hyperparameter models. …”
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Artificial intelligence for surgical outcome prediction in glaucoma: a systematic review by Zeena Kailani, Lauren Kim, Joshua Bierbrier, Michael Balas, David J. Mathew, David J. Mathew

“…Studies were included if they applied AI models to glaucoma surgery outcome prediction.ResultsSix studies met inclusion criteria, collectively analyzing 4,630 surgeries. A variety of algorithms were applied, including random forests, support vector machines, and neural networks. …”
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Sustainable financial infrastructure and governance: A fuzzy multi-criteria decision-making analysis of open service innovation in unstable economies by Homa Molavi, Lihong Zhang, Mohammad Khanbabaei

“…This includes highlighting the role of regulatory sandboxes in fostering innovation while ensuring compliance, the importance of data governance in maintaining trust and stability in the financial system, and the impact of AI implementation and AI-driven algorithms in driving open innovation within an unstable banking and economic system. …”
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