A data-driven group retrosynthesis planning model inspired by neurosymbolic programming by Xuefeng Zhang, Haowei Lin, Muhan Zhang, Yuan Zhou, Jianzhu Ma

“…Inspired by human learning, our algorithm, akin to neurosymbolic programming, builds upon commonly used multi-step concepts such as cascade and complementary reactions and can evolve from practical experiences, enhancing the prediction model for fundamental and compositional reaction templates. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…In outdoor field experiments conducted under cloudy, low-light, and artificial lighting conditions, the model achieved localization errors of 2.43 mm (X-axis), 3.70 mm (Y-axis), and 1.28 mm (Z-axis), representing reductions of 19.27 %, 12.67 %, and 23.05 %, respectively. …”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Cox models showed consistent reductions in 30-day (HR = 0.199, 95% CI: 0.124–0.320, p < 0.001) and 90-day (HR = 0.230, 95% CI: 0.150–0.352, p < 0.001) mortality. …”
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Time-delayed vibration control and parameter optimization of semi-active vehicle suspension designed for random road excitation by Yong Guo, Yong-Jing Li, Yan-Bo Wei

“…Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension systems. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The research highlights recent advancements, such as AI-assisted transaction validation and adaptive consensus algorithms, as promising directions for blockchain scalability and security. …”
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The quantification of percentage filling of gutta-percha in obturated root canal using image processing and analysis by Pravin R. Lokhande, S. Balaguru

“…Percentage filling of the obturated root canal using X-ray radiography (Dentist's prediction) and proposed algorithm results of the present study were compared. …”
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Hyperspectral Reconstruction Method Based on Global Gradient Information and Local Low-Rank Priors by Chipeng Cao, Jie Li, Pan Wang, Weiqiang Jin, Runrun Zou, Chun Qi

“…It combines reconstruction algorithms to recover hyperspectral data from low-dimensional measurement images. …”
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Identification and validation of parthanatos-related genes in end-stage renal disease by Xuan Dai, Lianfang Yuan

“…Two machine learning algorithms identified candidate genes, refined through ROC analysis. …”
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Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

“…Phytoplankton species biomass data were collected concurrently using standard inverted microscope counts. The SVR algorithm outperformed the other algorithms in predicting phytoplankton abundance and composition in Lake Kinneret, based on the FP measurements. …”
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MolNexTR: a generalized deep learning model for molecular image recognition by Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun, Hao Chen, Hanyu Gao

“…In addition, it employs a series of novel augmentation algorithms to significantly enhance the robustness and performance of the model.…”
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Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…Another major challenge is the technical limitations of AI. While AI algorithms are capable of analyzing vast amounts of data, they cannot always properly adapt to a changing market environment or predict consumer behavior in non-standard situations. …”
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Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities by Gift Echefu, Rushabh Shah, Zanele Sanchez, John Rickards, Sherry-Ann Brown

“…Additional application opportunities for AI in cardio-oncology involve multimodal cardiovascular imaging, where algorithms can also utilize imaging input to generate predictive risk profiles for cancer patients. …”
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Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism. by John Archer, Jan Weber, Kenneth Henry, Dane Winner, Richard Gibson, Lawrence Lee, Ellen Paxinos, Eric J Arts, David L Robertson, Larry Mimms, Miguel E Quiñones-Mateu

“…In this study, HIV-1 co-receptor usage was predicted for twelve patients scheduled to start a maraviroc-based antiretroviral regimen. …”
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Machine Learning (ML) Based Repair-Count and Periodic Maintenance Policy for Multipurpose CNC Machinery by Alifin Fakhri Ikhwanul, Winarno, Fasa Nadia, Darajatun Rizki Achmad, Kusnadi, Safariyani Eva

“…Several censored data were utilized to predict failure times using machine learning algorithms, such as process temperature, air temperature, rotational speed, and torque. …”
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Machine learning for clustering and classification of early knee osteoarthritis using single-leg standing kinematics by Ui-Jae Hwang, Kyu Sung Chung, Sung-Min Ha

“…This study investigated the application of machine learning techniques to single-leg standing (SLS) kinematics to classify and predict EOA. (1) To identify distinct groups based on SLS kinematic patterns using unsupervised learning algorithms, (2) to develop supervised learning models to predict EOA status, and (3) to identify the most influential kinematic variables associated with EOA. …”
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Synthetic Data Generation for AI-Informed End-of-Line Testing for Lithium-Ion Battery Production by Tessa Krause, Daniel Nusko, Johannes Rittmann, Luciana Pitta Bauermann, Moritz Kroll, Carlo Holly

“…To make these predictions, we implement artificial intelligence algorithms to extract information from the measurements. …”
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Machine-learning models for differentiating benign and malignant breast masses: Integrating automated breast volume scanning intra-tumoral, peri-tumoral features, and clinical info... by Meixue Dai, Yueqiong Yan, Zhong Li, Jidong Xiao

“…Combining radiomics with clinical features further enhanced predictive performance. The LGBM model outperformed the other algorithms across subgroups, achieving a maximum AUC of 0.909, an accuracy of 0.878, and an F1-score of 0.971. …”
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Explainable Feature Engineering for Multi-class Money Laundering Classification by Petre-Cornel GRIGORESCU, Antoaneta AMZA

“…This paper provides insight into typical money laundering typologies used in the financial crime domain and provides a concrete set of methods through the use of which fraudulent transactions may be classified using traditional machine learning algorithms and proving the efficacy of tree-based models in not only predictive power, but also explainability and ease of interpretation of results.…”
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AI-powered literature search: some observations and concerns by Farooq Azam Rathore, Fareeha Farooq

“…They should clearly outline their article selection criteria and summarization algorithms. This should be clearly displayed at the appropriate place at the website…”
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Simulations of Microwave Land Surface Emissivity Using FengYun-3D Microwave Radiation Imager Data: A Case in the Tibetan Plateau by Yonghong Liu, Fuzhong Weng, Fei Tang, Rui Li, Yongming Xu, Yang Han, Jun Yang, Qingyang Liu

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