The use of web resources for metabolomics in horticultural crops by Esra Karakas, Mustafa Bulut, Alisdair R. Fernie

“…Moreover, the application of machine learning algorithms to these web resources has further optimized data interpretation, enabling more accurate prediction of metabolic profiles. …”
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Dynamic Simulation and Comprehensive Quantitative Evaluation of Rural Tourism Core Competitiveness Based on Neural Network by Shiyuan Gan

“…This paper first designs the neural network algorithm model, then analyzes the dynamic simulation model and comprehensive quantitative analysis, and then uses the artificial neural network algorithm to analyze and predict the core competitiveness of rural tourism. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). …”
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Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features by Yanping Yang, Jiacheng Shen, Sulan Wei, Maosong Ye, Xing Zhao, Jian Zhou, Lin Tong, Jie Hu, Yuanlin Song, Shengdi Wu, Nuo Xu

“…The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. …”
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Clinical utility of artificial intelligence–augmented endobronchial ultrasound elastography in lymph node staging for lung cancerCentral MessagePerspective by Yogita S. Patel, BSc, Anthony A. Gatti, PhD, Forough Farrokhyar, MPhil, PhD, Feng Xie, PhD, Waël C. Hanna, MDCM, MBA

“…NeuralSeg was able to predict 98 of 143 true negatives and 34 of 44 true positives, resulting in an overall accuracy of 70.59% (95% CI, 63.50-77.01), sensitivity of 43.04% (95% CI, 31.94-54.67), specificity of 90.74% (95% CI, 83.63-95.47), positive predictive value of 77.27% (95% CI, 64.13-86.60), negative predictive value of 68.53% (95% CI, 64.05-72.70), and area under the curve of 0.820 (95% CI, 0.758-0.883). …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles by Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai

“…Our analyses revealed that the Random Forest algorithm exhibited the highest predictive accuracy, with AUC values of 0.809 for kidney stones, 0.99 for ureter stones, and 0.775 for multiple location stones. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Among the ten models tested, the LightGBM algorithm exhibited superior performance, with an AUC of 0.853 in the test cohort. …”
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Dynamic forecasting module for chronic graft-versus-host disease progression based on a disease-associated subpopulation of B cells: a multicenter prospective studyResearch in cont... by Yuanchen Ma, Jieying Chen, Zhiping Fan, Jiahao Shi, Gang Li, Xiaobo Li, Tao Wang, Na Xu, Jialing Liu, Zhishan Li, Heshe Li, Xiaoran Zhang, Dongjun Lin, Wu Song, Qifa Liu, Weijun Huang, Xiaoyong Chen, Andy Peng Xiang

“…Consequently, identifying appropriate immune cell subsets or molecules as prognostic or predictive biomarkers for cGVHD is essential. Methods: Building on the pivotal role of B-cell homeostasis in cGVHD progression, we integrated spectral flow cytometry with advanced machine learning algorithms to systematically analyze the relationship between B cells and cGVHD progression. …”
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The Measurement of Vital Signs in Pediatric Patients by Lifelight Software in Comparison to the Standard of Care: Protocol for the VISION-Junior Observational Study by Gauri Misra, Simon Wegerif, Louise Fairlie, Melissa Kapoor, James Fok, Gemma Salt, Jay Halbert, Ian Maconochie, Niall Mullen

“…Early data will be used to refine the algorithms. A separate dataset will be retained to test the performance of the app against predefined targets. …”
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Detection of Defects in Polyethylene and Polyamide Flat Panels Using Airborne Ultrasound-Traditional and Machine Learning Approach by Artur Krolik, Radosław Drelich, Michał Pakuła, Dariusz Mikołajewski, Izabela Rojek

“…Furthermore, ML models are adaptable, allowing the same trained algorithms to work on various material batches or panel types with minimal retraining. …”
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Enactivism, Health, AI, and Non-Neurotypical Individuals: Toward Contextualized, Personalized, and Ethically Grounded Interventions by Jordi Vallverdú

“…Drawing on relevant philosophical literature, empirical studies, and cross-disciplinary debates (including the friction and potential synergies between predictive processing and enactivism), we argue that AI solutions grounded in enactivist thinking can more effectively honor user autonomy, acknowledge the embodied nature of neurodiverse cognition, and avoid reductive standardizations. …”
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A Multi-Objective Optimization Method for Carbon–REC Trading in an Integrated Energy System of High-Speed Railways by Wei-Na Zhang, Zhe Xu, Ying-Yi Hong, Fang-Yu Liu, Zhong-Qin Bi

“…Benchmark analysis demonstrates superior economic–environmental synergy, achieving a 23.90% cost reduction (USD 923,152 annual savings) and 24.02% lower emissions (693,452.5 kg CO₂ reduction) versus conventional systems. …”
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Epidemiological and clinical characteristics of bacterial co-detection in respiratory syncytial virus-positive children in Wenzhou, China, 2021 to 2023 by Xiaoxiao Qu, Xuanmei Ye, Jian Yu, Feifei Zheng, Yatian Tang, Fangling Yuan, Qipeng Xie

“…Feature selection using the Boruta algorithm, combined with XGBoost modeling and SHAP interpretation, further confirmed that length of stay, WBC count, neutrophil count, and IgE were the most important predictive variables. …”
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Integrative multiomics analysis reveals the subtypes and key mechanisms of platinum resistance in gastric cancer: identification of KLF9 as a promising therapeutic target by Pengcheng Zhang, Lexin Wang, Haonan Lin, Yihui Han, Jingfang Zhou, Hang Song, Peng Wang, Huanhuan Tan, Yajuan Fu

“…Localization and functional evaluation were conducted at the single-cell and spatial transcriptomics levels, and predictive models were developed using machine learning techniques. …”
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Latest Advancements in Credit Risk Assessment with Machine Learning and Deep Learning Techniques by Soni Umangbhai, Jethava Gordhan, Ganatra Amit

“…The goal is to help develop novel algorithms that outperform existing methods. Even a slight improvement in defaulter prediction rates could significantly influence society by saving millions for lenders.…”
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Optimizing Spatial Complexity of the Hard Decision Decoder Based on Hash and Syndrome Decoding (HSDec) by Seddiq El Kasmi Alaoui, Tarik Chanyour, Hamza Faham, Said Nouh

“…The results demonstrated significant memory reduction rates and coding gains ranging from 0.8 dB to 2.8 dB over the AWGN channel and from 14 dB to 32 dB over the Rayleigh channel, confirming the robustness of the algorithm under different channel conditions. …”
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A Novel Green Logistics Vehicle Scheduling Method Against Road Congestion Utilizing Vehicle–Road–Cloud Collaborative Technology by Rui Zheng, Zhiwei Zhu, Xiaolu Ma, Ruiyang Shi, Zibao Lu

“…To solve this model, an initial solution is constructed using an energy-saving algorithm, while exploring a Cauchy variational strategy and a parallel local search to propose an improved adaptive large neighborhood search (ALNS) algorithm. …”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Exploring qubit-ADAPT-VQE for materials discovery in direct air capture by Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner

“…Quantum computing can potentially accelerate the discovery of solid sorbents for DAC by predicting molecular binding energies. In this work, we explore algorithms for predicting gas adsorption in metal–organic frameworks using a quantum computer. …”
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