DESIGN HYBRID META-HEURISTIC APPROACHES FOR IMPROVED RELIABILITY OPTIMIZATION by Shakuntla Singla, Manisha Rani, Shilpa Rani, A. K. Lal

“…Additionally, RGA and GWO showed better integration and R2 dispersion values, making them more effective for practical failure data analysis. …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

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Inversion of SPAD Values of Pear Leaves at Different Growth Stages Based on Machine Learning and Sentinel-2 Remote Sensing Data by Ning Yan, Qu Xie, Yasen Qin, Qi Wang, Sumin Lv, Xuedong Zhang, Xu Li

“…Subsequently, four machine learning algorithms—K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Machine (SVM), and an Optimized Integrated Algorithm (OIA)—were employed to develop SPAD retrieval models, and the performance differences across various input combinations and models were systematically evaluated. …”
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CYLD as a key regulator of myocardial infarction-to-heart failure transition revealed by multi-omics integration by Jingya Xu, Jingya Xu, Zhonghua Dong, Zhaodong Li, Xuan Wang, Xuan Wang

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Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy by Guangzong Li, Yuesen Zhang, Di Li, Manhong Zhao, Lin Yin

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Enhanced Dynamic Network DEA: A Novel Algorithm for Sustainable Development Efficiency Assessment in “Internet Plus Logistics” Sector by Yingli Wang, Guobin Qiu, Jing Wang, Qi Sun

“…This methodology leverages a comprehensive evaluation indicator system, emphasizing waterway, highway, and railway logistics outputs. The integration of custom algorithms into the CCR and BCC models has provided a deeper insight into efficiency trends and highlighted the need for a shift to an intensive economic model. …”
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Deep learning (DL)‐based advancements in prostate cancer imaging: Artificial intelligence (AI)‐based segmentation of 68Ga‐PSMSA PET for tumor volume assessment by Sharjeel Usmani, Khulood Al Riyami, Subash Kheruka, Shah P Numani, Rashid al Sukaiti, Maria Ahmed, Nadeem Pervez

“…AI algorithms, such as deep learning‐based models, have shown remarkable performance in automating tumor segmentation tasks with high accuracy and efficiency. …”
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Global Cross-Market Trading Optimization Using Iterative Combined Algorithm: A Multi-Asset Approach with Stocks and Cryptocurrencies by Kansuda Pankwaen, Sukrit Thongkairat, Worrawat Saijai

“…This study presents an advanced adaptive trading framework that integrates Deep Reinforcement Learning (DRL) with the Iterative Model Combining Algorithm (IMCA) to overcome the critical limitations of static ensemble methods in global portfolio optimization. …”
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Artificial Intelligence Algorithms and Their Current Role in the Identification and Comparison of Gleason Patterns in Prostate Cancer Histopathology: A Comprehensive Review by Usman Khalid, Jasmin Gurung, Mladen Doykov, Gancho Kostov, Bozhidar Hristov, Petar Uchikov, Maria Kraeva, Krasimir Kraev, Daniel Doykov, Katya Doykova, Siyana Valova, Lyubomir Chervenkov, Eduard Tilkiyan, Krasimira Eneva

“…Our paper explores the evolving role of AI in prostate cancer histopathology, with a key focus on outcomes and the reliability of various AI algorithms for Gleason pattern assessment. …”
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Modelling and Simulation of a 3MW, Seventeen-Phase Permanent Magnet AC Motor with AI-Based Drive Control for Submarines Under Deep-Sea Conditions by Arun Singh, Anita Khosla

“…A MATLAB/Simulink framework was developed to model the motor, whose drive system leverages an AI-optimised dual fuzzy-PID controller refined using the Harmony Search Algorithm. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

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State-of-the-Art Deep Learning Algorithms for Internet of Things-Based Detection of Crop Pests and Diseases: A Comprehensive Review by Jean Pierre Nyakuri, Celestin Nkundineza, Omar Gatera, Kizito Nkurikiyeyezu

“…Therefore, to tackle these challenges, harnessing advanced technologies such as artificial intelligence (AI), Machine Learning/Deep Learning (ML/DL), and Internet of Things (IoT) is essential for managing and mitigating agriculture hazards. …”
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Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology by Chao-Ming Wang, Cheng-Hao Shao, Yu-Ching Lin

“…The proposed interactive exercise and leisure system is developed by integrating motion-sensing interfaces and real-time object detection using the YOLO algorithm. …”
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Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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Overcoming the challenges of data integration in ecosystem studies with machine learning workflows: an example from the Santos project by Gustavo Fonseca, Danilo Candido Vieira

“… Integrating intricate environmental data within a unified analytical framework for extensive conservation and monitoring initiatives encounters several challenges. …”
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Overcoming the challenges of data integration in ecosystem studies with machine learning workflows: an example from the Santos project by Gustavo Fonseca, Danilo Candido Vieira

“… Integrating intricate environmental data within a unified analytical framework for extensive conservation and monitoring initiatives encounters several challenges. …”
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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

“…ObjectiveThis study aimed to address these challenges using an advanced preprocessing algorithm to enhance the accuracy, efficiency, and standardization of eye region cropping for clinical workflows and AI data preprocessing. …”
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Enhancing stochastic optimal power flow with modified cheetah optimizer for integrating renewable energy sources by Majid Saeidi, Taher Niknam, Mohsen Zare, Zulfiqar Ali Memon

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Integrating equity, diversity, and inclusion throughout the lifecycle of artificial intelligence for healthcare: a scoping review. by Ting Wang, Elham Emami, Dana Jafarpour, Raymond Tolentino, Genevieve Gore, Samira Abbasgholizadeh Rahimi

“…A comprehensive framework is needed to ensure that EDI principles are considered throughout the AI lifecycle. Future research could focus on strategies to reduce algorithmic bias, assess the long-term impact of EDI integration, and explore policy implications to ensure that AI technologies are ethical, responsible, and beneficial for all.…”
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Stock portfolio optimization using hill climbing and simple human learning optimization algorithms as a decision support system by Suyash S. Satpute, Amol C. Adamuthe, Pooja Bagane

“…The novelty in methodology is ‘hybridizing’ nature-inspired algorithms for optimized portfolio selection with two independent modules: intrinsic value of stocks and financial health analysis. …”
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