Deep reinforcement learning for inverse inorganic materials design by Christopher Karpovich, Elton Pan, Elsa A. Olivetti

“…We apply template-based crystal structure prediction to suggest feasible crystal structure matches for target inorganic compositions identified by our machine learning (ML) algorithms to highlight the plausibility of the identified target compositions. …”
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Risk Measurement of TAVR Surgical Complications Based on Unbalanced Multilabel Classification Approaches by Yue Zhang, Yuantao Xie

“…The model used in this paper bridges the gap between medical risk prediction and insurance actuarial science, provides a practical data modelling foundation and algorithmic support for the future development of post-operative complication insurance products that precisely align with clinical risk.…”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. Distinct AU patterns were found for all five phases, with gradient boosting machine and random forest models achieving the highest predictive accuracy. …”
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Parallel Implicit Runge-Kutta Methods for Stiff ODEs by Bashir Khalaf, Abdulhabib Murshid

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GPU Accelerated Trilateral Filter for MR Image Restoration by Suthir Sriram, Nivethitha Vijayaraj, T. Srilekha, M. Praveena, Thangavel Murugan

“…MRI serves as a non-invasive imaging tool to diagnose brain diseases yet the noise produced during its acquisition phase degrades image quality so that diagnosis accuracy suffers. Reduction of noise becomes essential for both clinical diagnostic procedures and computer-assisted medical analysis practices which require tissue classification and registration and segmentation algorithms. …”
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Artificial intelligence-driven metabolic engineering is applied to the development of active ingredients in Traditional Chinese Medicine by Zhang Guoqi, Wang Juan

“…In this paper, we introduce AI-driven machine learning algorithms in prediction models, and also review recent research progress on AI-assisted metabolic engineering design and production of high-value compounds, focusing on how to use AI methods to achieve directed evolution of strains.…”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. …”
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A reproducible approach for the use of aptamer libraries for the identification of Aptamarkers for brain amyloid deposition based on plasma analysis. by Cathal Meehan, Soizic Lecocq, Gregory Penner

“…Results were analysed using multiple machine learning algorithms from the Scikit-learn package along with clinical variables including cognitive status, age and sex to create predictive models. …”
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Legal Analysis of AI-Generated Creations: Copyright Law Perspectives by Praja Chrisna Bagus Edhita, Hakim Hary Abdul, Basri, Kurniaty Yulia, Sari Elvira Purnama

“…Legal analysis shows that AI is just a computer programming tool that performs tasks based on human commands. AI uses algorithms and computer training for recognition, prediction, and decision-making. …”
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Utilizing MV-FLOW™ and multidimensional ultrasound characteristics for prognosticating FET outcomes in RIF patients: Study Protocol for a cross-sectional study. by Ying Zhou, Li-Ying Liu, Hua-Ju Yang, Yuan-Yuan Lai, Di Gan, Jie Yang

“…Based on the above, this study aims to establish and validate a clinical prediction model for FET outcomes using support vector classification (SVC) algorithms, based on MV-FLOW™ and multidimensional transvaginal ultrasound imaging features. …”
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Uncertainty of industrial noise measurement at distant locations from the source by Tadeusz Wszołek

“…The paper deals with some real word data of partial uncertainties of noise prediction and measurement from large industry and impulse sound sources, taken in different meteorological conditions. …”
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An Improved Kernelized Correlation Filter for Extracting Traffic Flow in Satellite Videos by Dudu Guo, Hongbo Shuai, Jie Zhang, Yang Wang, Miao Sun

“…Second, we utilized the Kalman filter for trajectory prediction to reduce the loss of target during vehicle tracking. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…To investigate the effect of sampling frequency on the performance of detection methods, we designed a processing framework to evaluate different classification algorithms on versions of a challenging dataset obtained by down‐sampling the original data at various rates. …”
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Hybrid Laminar Flow Control Optimizations for Infinite Swept Wings by Yayun Shi, Xiayu Lan, Tihao Yang

“…The Reynolds-averaged Navier-Stokes (RANS) solver coupled with the linear stability theory is applied for the laminar-turbulent transition prediction, and the traditional optimization method based on evolutionary algorithms is applied for laminar flow wing optimization. …”
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Soil liquefaction assessment using machine learning by Gamze Maden Muftuoglu, Kaveh Dehghanian

“…Compared to other approaches, the study assesses how well these algorithms predict soil liquefaction potential. Early findings show that the algorithms perform well, demonstrating their capacity to identify non-linear connections and improve prediction accuracy. …”
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Association between international normalized ratio-to-albumin ratio and mortality in critically ill patients with gastrointestinal bleeding: a retrospective MIMIC-IV database study by Xingyi Yang, Shasha Ying, Lihong Lv, Yishu Ji, Jiaqian Ying, Huyan Ke

“…Subgroup analyses were performed to examine potential interaction effects, and feature selection was executed via the Boruta algorithm. Finally, a prognostic nomogram integrating the key predictors was developed. …”
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Exploring the Role of Artificial Intelligence in Detecting Advanced Persistent Threats by Pedro Ramos Brandao

“…By leveraging machine learning algorithms and data analytics, AI systems can identify patterns and anomalies that are indicative of sophisticated cyber-attacks. …”
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TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

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A Survey of Loss Functions in Deep Learning by Caiyi Li, Kaishuai Liu, Shuai Liu

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Evaluation of Information Indicators of Quantization Noise Generated by Speech Signal Analogue-Digital Conversion by V. K. Zheleznyak, K. J. Rahanov, Y. R. Adamovskiy

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