Showing 801 - 820 results of 4,226 for search '(( value integration algorithm ) OR ( ai integration algorithm ))', query time: 0.25s Refine Results
  1. 801
  2. 802

    ICBoost: An XGBoost-Based Unbiased Transformed Algorithm for Survival Regression by Jingyi Zhang, Shishun Zhao, Yang Xu, Tao Hu

    Published 2025-01-01
    “…Therefore, we present ICBoost, a novel survival algorithm that integrates regression trees and ensemble methods specifically designed for interval-censored data. …”
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  3. 803

    A Brand-New Algorithm for Mapping Algal Biomass in Lakes by Zhengyang Yu, Ronghua Ma, Minqi Hu, Kun Xue, Zhigang Cao, Junfeng Xiong

    Published 2025-01-01
    “…It can be summarized in step 1: inversion of surface chlorophyll a (Chla), step 2: inversion of diffuse attenuation coefficient of the photosynthetic active radiation [Kd(PAR)], and step 3: estimation of algal biomass with a pretrained generalized additive model. The proposed algorithm outperforms the result-oriented and process-oriented methods in terms of accuracy in 3 lakes (the root mean square error [RMSE] values for datasets of Lake Hongze, Lake Taihu, and Lake Chaohu were 5.09, 8.21, and 3.90 mg/m2, respectively). …”
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  4. 804

    Data Aggregation and Scheduling to Optimize Information Freshness In Multi-Hop IoT Networks by Xueling Wu, Long Qu, Maurice J. Khabbaz

    Published 2025-01-01
    “…Simulation results demonstrate that the proposed CGA consistently outperforms EASA, the Genetic Algorithm (GA), and the Juventas Algorithm, achieving an average deviation of only 1.84% from the global optimal solution.…”
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  5. 805
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    AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review by Xuanchi Guo, Yuhan Shao

    Published 2025-08-01
    “…This review will focus on the fusion of AI-driven multimodal data analysis (e.g., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. …”
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  8. 808

    Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

    Published 2025-07-01
    “…This study employs an integrated data-driven approach to optimize MXene-based aqueous ionic liquids by varying system temperature and MXene mass fraction (MF). …”
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  9. 809

    AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

    Published 2025-01-01
    “…This study introduces a novel DE-FinFET featuring a stepped field plate to improve overall performance of device. Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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  10. 810

    A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection by Saeid Sheikhi, Mohammad Taghi Kheirabadi, Amin Bazzazi

    Published 2020-12-01
    “…K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. …”
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  11. 811
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    “Voice is the New Blood”: a discourse analysis of voice AI health-tech start-up websites by Alden Blatter, Hortense Gallois, Emily Evangelista, Yael Bensoussan, Bridge2AI-Voice Consortium, Jean-Christophe Bélisle-Pipon, Yael E. Bensoussan, Olivier Elemento, Jean-Christophe Bélisle-Pipon, David Dorr, Satrajit Ghosh, Alistair Johnson, Phillip Payne, Maria E. Powell, Anaïs Rameau, Vardit Ravitsky, Alexandros Sigaras

    Published 2025-05-01
    “…However, descriptions of voice datasets used to train algorithms vary widely and are often absent, reflecting broader gaps in acoustic and ethical standards for voice data collection and insufficient incentives for start-ups to disclose key data details.DiscussionStart-ups play a crucial role in the research, development, and marketization of voice AI health-tech, prefacing the integration of this new technology into healthcare systems. …”
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  13. 813

    Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

    Published 2024-08-01
    “…To isolate and quantify the crack region, this research combines image thresholding, morphological operations, and contour detection with the convex hulls method and forms a novel algorithm. Two explainable AI (XAI) tools, local interpretable model-agnostic explanations (LIMEs) and gradient-weighted class activation mapping++ (Grad-CAM++) are integrated with the proposed method to enhance result clarity. …”
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  14. 814

    Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

    Published 2025-01-01
    “…Feature selection methods—such as filter, wrapper, and embedded techniques—play a critical role in enhancing the precision of cancer diagnostics by identifying relevant biomarkers. The integration of multi-omics data and ML algorithms facilitates a more comprehensive understanding of tumor heterogeneity, advancing both diagnostics and personalized therapies. …”
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  15. 815

    AI-Enabled Digital Marketing in Startups: A Systematic Review of Global Practices and Egyptian Implementation Challenges by Wael Bedda, Heba Al-Ashry, Hamed Ead

    Published 2025-06-01
    “…The study also examines Egypt’s entrepreneurial ecosystem, noting government-backed incubators like INTILAC and a youth-driven, tech-savvy population as potential enablers for AI integration. Challenges such as ethical concerns, algorithmic bias, and cultural readiness still persist. …”
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  16. 816

    Whose Bias is it, Anyway? The Need for a Four-Eyes Principle in AI-Driven Competion Law Proceedings by Jerome De Cooman

    Published 2024-12-01
    “…The argument is that although the use of algorithms increases procedural fairness by removing noise and cognitive biases from the decision-making process, the overall impact on procedural fairness remains far from clear given that the introduction of AI systems in public administration might perniciously generates new type of biases or harmful behaviours. …”
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  17. 817

    The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models by Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed

    Published 2025-05-01
    “…Although artificial intelligence (AI) has showed amazing promise in breast cancer prediction mainly machine learning (ML) algorithms as well as deep learning (DL), practical use of these models is greatly hampered by their lack of interpretability and transparency. …”
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  18. 818

    Enhancing action recognition in educational settings using AI-driven information systems for public health monitoring by Changchun Lu, Han Ruijuan

    Published 2025-07-01
    “…IntroductionThe integration of Artificial Intelligence (AI) into educational environments is revolutionizing action recognition, offering a transformative opportunity to enhance public health monitoring. …”
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  19. 819

    Gamified Engagement for Data Crowdsourcing and AI Literacy: An Investigation in Affective Communication Through Speech Emotion Recognition by Eleni Siamtanidou, Lazaros Vrysis, Nikolaos Vryzas, Charalampos A. Dimoulas

    Published 2025-02-01
    “…Additionally, 50% of participants identified social interaction features, such as collaboration, as most beneficial for fostering motivation and commitment. The integration of these elements supports reliable and extensive data collection and the advancement of AI algorithms while concurrently developing various skills, such as emotional speech articulation and digital literacy. …”
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  20. 820

    AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes by Ang Li, Yunxin Wang, Hongxu Chen

    Published 2025-06-01
    “…To address these issues, we introduce a hybrid machine learning (ML) framework that integrates the Wolf Pack Search Algorithm Dynamic Random Forest (WPSA-DRF) with a RoBERTa-based LLM to enhance the accuracy of cardiovascular disease predictions. …”
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