Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare by Nargish Parvin, Sang Woo Joo, Jae Hak Jung, Tapas K. Mandal

“…In diagnostics, AI systems synthesize multimodal inputs combining imaging, molecular markers, and clinical data—to improve diagnostic precision and support early disease detection. …”
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Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study by Maryam Ramezani, Mohammadreza Mobinizadeh, Ahad Bakhtiari, Hamid R. Rabiee, Maryam Ramezani, Hakimeh Mostafavi, Alireza Olyaeemanesh, Ali Akbar Fazaeli, Alireza Atashi, Saharnaz Sazgarnejad, Efat Mohamadi, Amirhossein Takian

“…Among algorithms, the Linear Discriminant algorithm as classification model was selected as the best model due to its high accuracy in both testing and training phases, its strong performance in identifying key features, and its good generalizability to new data. …”
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Using Calibration Transfer Strategy to Update Hyperspectral Model for Quantitating Soluble Solid Content of Blueberry Across Different Batches by Biao Chen, Xuhuang Huang, Shenwen Tan, Guangjun Qiu, Huaiyin Lin, Xuejun Yue, Junzhi Chen, Wenshan Zhong, Xuantian Li, Le Zhang

“…Different sample batches and differences in hyperspectral image acquisition environments may lead to a significant decline in the performance of hyperspectral detection models. …”
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Easy Data Augmentation untuk Data yang Imbalance pada Konsultasi Kesehatan Daring by Anisa Nur Azizah, Misbachul Falach Asy'ari, Ifnu Wisma Dwi Prastya, Diana Purwitasari

“…Hasil parameter EDA terbaik diperoleh dengan menambahkan nilai 0,1 pada semua teknik EDA mendapatkan 88,86% dan 88,44% untuk akurasi dan nilai F1-score. …”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…Results On the HECKTOR dataset, ES-UNet achieved a Dice Similarity Coefficient (DSC) of 76.87%, outperforming baseline models including 3D UNet, 3D UNet 3+, nnUNet, and Swin UNETR. …”
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Ranking polycystic ovarian syndrome (PCOS) drugs using degree-based indices in QSPR models and CRITIC-driven MCDM methods by Muhammad Waheed Rasheed, Abid Mahboob, Laiba Amin, Aysha Hussain

“…We rate these medications using three different multi-criteria decision-making (MCDM) algorithms: CRITIC, CoCoSo, and MABAC. …”
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Robust multisynchrosqueezing transform time frequency technologies with application to fault diagnosis by Haibin Wang, Junbo Long, Changshou Deng, Youxue Zhou

“…Time-frequency analysis (TFA) methods serve as effective tools for analyzing stationary signals.Multisynchrosqueezing Transform (MSST) represents a novel post-processing TFA technology designed for pulse-like signals or noisy environments, aiming to enhance the concentration of time–frequency energy.However, in environments characterized by strong impulsive α stable distribution noise, the time–frequency concentration of existing MSST algorithms, a critical performance metric, is significantly compromised, leading to substantial local deviations. …”
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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. …”
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Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling Devices by Mudassar Liaq, Waleed Ejaz

“…FL enables collaborative model training across decentralized IoT devices by keeping data local, eliminating the need for centralized data collection. …”
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Emerging technologies and applications in multimodality imaging for ischemic heart disease: current state and future of artificial intelligence by Praveen Kumar Chandra Sekar, Ramakrishnan Veerabathiran

“…Future directions include AI-driven decision support systems and personalized medicine approaches. …”
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The moderating role of personalized recommendations in the trust–satisfaction–loyalty relationship: an empirical study of AI-driven e-commerce by Noha Hassan, Mohamed Abdelraouf, Dina El-Shihy

“…It aims to explore how personalized AI features reshape consumer perceptions and decision-making. Design/methodology/approach A quantitative research approach was used to collect data from a diverse group of e-commerce users who had interacted with AI-based recommendation systems. …”
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Automated Cervical Cancer Screening Using Single-Cell Segmentation and Deep Learning: Enhanced Performance with Liquid-Based Cytology by Mariangel Rodríguez, Claudio Córdova, Isabel Benjumeda, Sebastián San Martín

“…The high accuracy and efficiency of DL models combined with effective segmentation can contribute to earlier detection and more timely intervention. …”
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State Estimation for Quadruped Robots on Non-Stationary Terrain via Invariant Extended Kalman Filter and Disturbance Observer by Mingfei Wan, Daoguang Liu, Jun Wu, Li Li, Zhangjun Peng, Zhigui Liu

“…Existing state estimation algorithms relying on multi-sensor fusion, such as those using IMU, LiDAR, and visual data, often face challenges on non-stationary terrains due to issues like foot-end slippage or unstable contact, leading to significant state drift. …”
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Translational medicine research on the role of key gene network modulation mediated by procyanidin B2 in the precise diagnosis and treatment of multiple sclerosis by Jian Liu, Meng Pu, Di Guo, Ying Xiao, Jin-zhu Yin, Dong Ma, Cun-gen Ma, Qing Wang

“…Methods The target genes of PCB2 and the disease-related target genes of MS were gathered from databases like GEO, GeneCards, OMIM, and DisGeNET. …”
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AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices by Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, Naveen Kumar SK, George K Stylios

“…This review explores the synergistic potential of AI‐driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real‐time sensing. …”
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Estimating the time of Highly Pathogenic Avian Influenza virus introduction into United States poultry flocks during the 2022/24 epizootic. by Amos Ssematimba, Sasidhar Malladi, Peter J Bonney, Kaitlyn M St Charles, Holden C Hutchinson, Melissa Schoenbaum, Rosemary Marusak, Marie R Culhane, Carol J Cardona

“…The estimated joint (i.e., all species combined) median of the MTFPS for different flocks was six days, the joint median most likely ACR was 6.8 newly infected birds per infectious bird per day, the joint median R0 was 13 and the joint median number of test days per flock was two. …”
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A review of machine learning and deep learning for Parkinson’s disease detection by Hajar Rabie, Moulay A. Akhloufi

“…However, challenges like the need for large and diverse datasets, data privacy concerns, and data quality in healthcare remain. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. …”
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Online calibration of LiDAR-camera extrinsic parameters of tunnel mapping system with depth-constrained vibration compensation by Han Hu, Ying Jiang, Zeyuan Dai, Rui Hao, Wenna Fan, Lihua Zhang, Xuming Ge, Bo Xu, Qing Zhu

“…Tunnel mapping systems are essential for tunnel inspection, integrating sensors like LiDAR, cameras, and odometers to enhance data accuracy. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Therefore, developing a more effective method to address pedestrian occlusion detection is essential for enhancing the performance of pedestrian detectors.MethodsProposed the Global Feature Focusing and Information Enhancement Network (GFFIE-Net). …”
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