Search Results - research algorithm

Harnessing artificial intelligence of things for cardiac sensing: current advances and network-based perspectives by Hao Ren, Hao Ren, Hao Ren, Fengshi Jing, Yongcong Ma, Ruining Wang, Chaocheng He, Yufan Wang, Jiandong Zhou, Yu Sun

“…A total of 2,128 papers were included in the analysis.ConclusionFrom our perspective, current advancements in AI-powered IoT cardiac sensors primarily focus on optimizing AI algorithms, such as deep learning techniques, and enhancing the functionality of smart wearable devices for precision medicine. …”
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AI-Driven Mapping System for Smart Parking Management Applications Using an INS-GNSS-Solid-State LiDAR-Monocular Camera Fusion Engine Empowered by HD Maps by Kai-Wei Chiang, Syun Tsai, Jou-An Chen, Surachet Srinara, Meng-Lun Tsai, Chih-Yun Hsieh, Jyun-Yang Hung, Chalermchon Satirapod, Naser El-Sheimy

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Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…This review highlights the need for continued innovation and coordinated efforts across research, policy, and education to overcome these barriers and support the global transition to more sustainable agricultural practices.…”
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Enhancing fibroblast–epithelial cell communications: Serpine2 as a key molecule in Fusobacterium nucleatum–promoted colon cancer by Xueke Li, Xueke Li, Simin Luo, Yifang Jiang, Qiong Ma, Fengming You, Fengming You, Qixuan Kuang, Xi Fu, Chuan Zheng

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Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages by Süreyya Betül Rufaioğlu, Ali Volkan Bilgili, Erdinç Savaşlı, İrfan Özberk, Salih Aydemir, Amjad Mohamed Ismael, Yunus Kaya, João P. Matos-Carvalho

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Transforming nano grids to smart grid 3.0: AI, digital twins, blockchain, and the metaverse revolutionizing the energy ecosystem by Herman Zahid, Adil Zulfiqar, Muhammad Adnan, Muhammad Sajid Iqbal, Anwar Shah, Usman Abbasi, Salah Eldeen Gasim Mohamed

“…This study systematically analyzes the application of advanced algorithms and technologies across all hierarchical subsystems—nanogrid 3.0, microgrid 3.0, VPP 3.0, and Smart Grid 3.0. …”
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Next-Gen UAV-Satellite Communications: AI Innovations and Future Prospects by Sherief Hashima, Ahmad Gendia, Kohei Hatano, Osamu Muta, Mostafa S. Nada, Ehab Mahmoud Mohamed

“…This paper comprehensively analyzes these challenges, offering innovative solutions and outlining future research directions to unlock the complete capabilities of 6G-enabled UAV-satellite communications. …”
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Scalable Clustering of Complex ECG Health Data: Big Data Clustering Analysis with UMAP and HDBSCAN by Vladislav Kaverinskiy, Illya Chaikovsky, Anton Mnevets, Tatiana Ryzhenko, Mykhailo Bocharov, Kyrylo Malakhov

“…The study aims to apply unsupervised clustering algorithms to ECG data to detect latent risk profiles related to heart failure, based on distinctive ECG features. …”
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Predicting Pathological Complete Response Following Neoadjuvant Therapy in Patients With Breast Cancer: Development of Machine Learning–Based Prediction Models in a Retrospective S... by Chun-Chi Lai, Cheng-Yu Chen, Tzu-Hao Chang

“…Model 3 added breast sonography response data to the clinical variables in model 1. Algorithms including logistic regression, random forest, support vector machines, and extreme gradient boosting were used. …”
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Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia by Yi Wei Chen, Shan He, Yu Wang, Lian Ying Hu, Qin Kai Chen, Si Yi Liu

“…Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. …”
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Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts by Emre Uysal, Gorkem Durak, Ayse Kotek Sedef, Ulas Bagci, Tanju Berber, Necla Gurdal, Berna Akkus Yildirim

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Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

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SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

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Double‐row suture‐bridge technique does not yield better clinical and radiological results than single‐row technique in patients older than 55 years at 2 years minimum follow‐up: A... by Vito Gaetano Rinaldi, Sassoli Iacopo, Federico Coliva, Antongiulio Favero, Alberto Bazzocchi, Marco Miceli, Stefano Di Paolo, Stefano Zaffagnini, Giulio Maria Marcheggiani Muccioli

“…While limitations exist, our findings contribute to understanding optimal surgical approaches, emphasizing individualized treatment based on patient characteristics and surgeon expertise. Further research, including randomized controlled trials with long‐term follow‐up, is needed to refine treatment algorithms and improve patient outcomes in rotator cuff surgery. …”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Traditional photogrammetry methods like structure-from-motion (SfM) or simultaneous localization and mapping (SLAM) can technically accomplish CVGL, but require a sufficiently dense collection of camera views in order to recover camera pose. This research proposes an alternative CVGL solution, a series of algorithmic operations which can completely automate the calculation of target camera pose via a less common photogrammetry method known as monoplotting, also called single camera resectioning. …”
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Machine learning models for discriminating clinically significant from clinically insignificant prostate cancer using bi-parametric magnetic resonance imaging by Hakan Ayyıldız, Okan İnce, Esin Korkut, Merve Gülbiz Dağoğlu Kartal, Atadan Tunacı, Şükrü Mehmet Ertürk

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Integrative identification of key genes governing Verticillium wilt resistance in Gossypium hirsutum using machine learning and WGCNA by Yufeng Lei, Jing Zhao, Siyuan Hou, Fufeng Xu, Chongbo Zhang, Dongchen Cai, Xiaolei Cao, Zhaoqun Yao, Sifeng Zhao

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Integrated Workflow for Drug Repurposing in Glioblastoma: Computational Prediction and Preclinical Validation of Therapeutic Candidates by Nazareno Gonzalez, Melanie Pérez Küper, Matías Garcia Fallit, Jorge A. Peña Agudelo, Alejandro Nicola Candia, Maicol Suarez Velandia, Ana Clara Romero, Guillermo Videla Richardson, Marianela Candolfi

“…This study aimed to develop and validate an integrated model for predicting GBM sensitivity to alternative chemotherapeutics and identifying new drugs and combinations with therapeutic potential. Research Design and Methods: We analyzed drug sensitivity data for 272 compounds from CancerRxTissue and employed in silico algorithms to assess blood-brain barrier permeability. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…Challenges persist in computational demands for online training and reinforcement learning’s exploration–exploitation trade-offs. Future research should prioritize adaptive algorithms for fatigue compensation, lightweight AI models for embedded deployment, and standardized benchmarking to bridge material-specific performance gaps. …”
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Machine Learning in Ambient Assisted Living for Enhanced Elderly Healthcare: A Systematic Literature Review by Aabid A. Mir, Ahmad S. Khalid, Shahrulniza Musa, Mohammad Faizal Ahmad Fauzi, Normy Norfiza Abdul Razak, Tong Boon Tang

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