Integrating Single‐Cell Transcriptomics and Machine Learning to Define an ac4C Gene Signature in Lung Adenocarcinoma by Yuan Wang, Wei Su, Guangyao Zhou, Yijie Wang, Chunnuan Wu, Pengpeng Zhang, Lianmin Zhang

“…Ten machine learning algorithms were applied to develop and validate an ac4C‐related gene signature (ARGSig) for prognosis prediction across multiple independent cohorts. …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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Parameter Estimation for Coupled Hydromechanical Simulation of Dynamic Compaction Based on Pareto Multiobjective Optimization by Wei Wang, Lu-Lu Zhang, Jin-Jian Chen, Jian-Hua Wang

“…Robustness of the back estimated parameters is further illustrated by a forward prediction. Results show that the back-analyzed soil parameters can reasonably predict lateral displacements and give generally acceptable predictions of dynamic compaction for an adjacent location. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…To screen for hub genes associated with OA, a combination of 10 machine learning algorithms and 113 algorithm compositions was integrated. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…Reinforcement Learning (RL) in CRs helps predict spectral changes and identify optimal transmission frequencies. …”
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Artificial intelligence models in corporate financial and accounting processes: systematic literature review by Deivi David Fuentes Doria, Aníbal Toscano Hernández, Johana Elisa Fajardo Pereira

“…The results suggest that supervised models are the most applied in the accounting and financial field, while the algorithms that have been most used are decision trees, support vector machines, random forests, neural networks, and logistic regressions, employed in specific areas of financial fraud, stock market predictions, and cash flow. …”
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Dose-Weighted Network Pharmacology: Evaluating Traditional Chinese Medicine Formulations for Lumbar Disc Herniation by Zhou C, Xiang T, Yu Y, Ma H, Liu C, Yang F, Yang L

“…These predictions were confirmed in animal studies, where YJD demonstrated the greatest reduction in thermal hyperalgesia and the most significant decrease in inflammatory markers, surpassing both TSD and PQT. …”
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Performance of a novel computer‐aided diagnosis system in the characterization of colorectal polyps, and its role in meeting Preservation and Incorporation of Valuable Endoscopic I... by Ejaz Hossain, Mohamed Abdelrahim, Andrea Tanasescu, Masayoshi Yamada, Hiroko Kondo, Shijemi Yamada, Ryuji Hamamoto, Atsushi Marugame, Yutaka Saito, Pradeep Bhandari

“…Recently, a novel AI algorithm for the characterization of polyps was developed by NEC Corporation (Japan). …”
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Modeling of erosion processes in open channels by M. R. Magomedova

“…A technique has been developed for predicting the general erosion of riverbeds and canals, composed of homogeneous and heterogeneous non-cohesive soils. …”
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Spectroscopic photoacoustic denoising framework using hybrid analytical and data-free learning method by Fangzhou Lin, Shang Gao, Yichuan Tang, Xihan Ma, Ryo Murakami, Ziming Zhang, John D. Obayemi, Winston O. Soboyejo, Haichong K. Zhang

“…Advanced methods, including learning-based approaches and analytical algorithms, have demonstrated promise but often require extensive training data and parameter tuning. …”
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Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Wen Yao Low, Nor Zaihar Yahaya, Ahmed Tijjani Dahiru, Temitope Ibrahim Amosa, Shehu Lukman Ayinla

“…Cost evaluations under critical peak tariffs indicate that both EMS algorithms achieved a 34 % cost saving compared to a grid-only system. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…The objective was to apply a classification method to predict WQI using Kinta River data in Malaysia and improve on existing models&#x2019; <inline-formula> <tex-math notation="LaTeX">$70-95\%$ </tex-math></inline-formula> accuracy range. …”
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Mechanical Ventilation Strategies in Buildings: A Comprehensive Review of Climate Management, Indoor Air Quality, and Energy Efficiency by Farhan Lafta Rashid, Mudhar A. Al-Obaidi, Najah M. L. Al Maimuri, Arman Ameen, Ephraim Bonah Agyekum, Atef Chibani, Mohamed Kezzar

“…Hybrid ventilation systems have demonstrated improved thermal comfort, with predicted mean vote (PMV) values ranging from –0.41 to 0.37 when radiant heating is utilized. …”
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Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling by Qi Qi, Yi Shang

“…We compare their performances in terms of predictive accuracies for the unobserved time points based on their selections of observations. …”
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Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China by Qingfeng Zhou, Chun Janice Wong, Xian Su

“…It is feasible to use these factors to predict area type to optimize the number of available bicycles, reduce operating costs, and improve utilization efficiency. …”
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Design and development of advanced Al-Ti-V alloys for beampipe applications in particle accelerators by Kamaljeet Singh, Kangkan Goswami, Raghunath Sahoo, Sumanta Samal

“…The present investigation reports the design and development of an advanced material with a high figure of merit (FoM) for beampipe applications in particle accelerators by bringing synergy between computational and experimental approaches. Machine-learning algorithms have been used to predict the phase(s), low density, and high radiation length of the designed Al-Ti-V alloys. …”
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CPP: a path planning method taking into account obstacle shadow hiding by Ruixin Zhang, Qing Xu, Youneng Su, Ruoxu Chen, Kai Sun, Fengchang Li, Guo Zhang

“…We also proposed a Minimum-Jerk Trajectory Optimization method with controllable path noise points, which enhanced path smoothness and reduced predictability. Comparative analysis showed that CPP significantly outperformed five other algorithms—RRT, Improved B-RRT, RRT*, Informed RRT*, and Potential Field-by reducing running time by 46.01% to 93.3%, increasing path safety by 10.42% to 83.44%, and improving path smoothness, making it particularly effective for path planning in tactical scenarios involving unmanned vehicles.…”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis by Lijuan Feng, Kaiyong Bai, Limeng He, Hao Wang, Wei Zhang

“…Additionally, a nomogram model was employed to predict the diagnostic ability of biomarkers for RA. …”
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