AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

“…Abstract In the context of smart homes, efficiently managing temperature control while optimizing energy consumption and ensuring data security remains a significant challenge. …”
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YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study by Qilei zhang, Zhe Li, Huiping Zhang, Ling Han, Shugang Zhao, Siyu Jia

“…In conclusion, YouTube videos exhibited higher audience engagement and video quality, yet improvements are needed on both platforms. In order to promote high-quality health information, it is essential to encourage the development of more professional content creators and to optimize platform algorithms.…”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Normalizing ApoE4 to total ApoE improved classification (sensitivity 94.3%, specificity 93.9%). …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…Radiomic models were established based on extracted features from tumor-dominant regions of interest (ROI) on CT images, while clinical models were developed using demographic characteristics and preoperative laboratory examinations. …”
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‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion by Manash Sarma, Subarna Chatterjee

“…Abstract Objective The present study explores the classification of Alzheimer’s disease (AD) stages, encompassing cognitive normalcy, Mild Cognitive Impairment (MCI), and AD/Dementia, through the application of Machine Learning (ML) multiclassification algorithms. This investigation utilizes blood gene expression datasets obtained from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the National Center for Biotechnology Information (NCBI). …”
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A Review of Enhancement Techniques for Cone Beam Computed Tomography Images by Hassn Mazin Al-alaaf, Mohammed Sabah Jarjees

“…These methods encompass various mathematical algorithms, machine learning approaches, and hybrid models, which aim to mitigate the imperfections present in CBCT data while preserving diagnostically relevant information. …”
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Research on Credit Risk Prevention in Supply Chain Finance Driven by Blockchain by Lin Kejing

“…Distributed ledger technology is utilized through blockchain to ensure the transparency and traceability of information, while smart contracts optimize the credit execution and supervision process, playing a key role in preventing and controlling credit risks. …”
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HybridBranchNetV2: Towards reliable artificial intelligence in image classification using reinforcement learning. by Ebrahim Parcham, Mansoor Fateh, Vahid Abolghasemi

“…By dynamically adjusting feature extraction based on feedback from the environment, the model improves adaptability, while graph-based methods allow for a more comprehensive analysis of object relationships. …”
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Artificial Intelligence Applications in Pediatric Craniofacial Surgery by Lucas M. Harrison, Ragan L. Edison, Rami R. Hallac

“…Artificial intelligence is rapidly transforming pediatric craniofacial surgery by enhancing diagnostic accuracy, improving surgical precision, and optimizing postoperative care. …”
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Artificial intelligence applications in pediatric ophthalmology: A comprehensive review by Anupama Janardhanan, Meenakshi Ravindran, Allapitchai Fathima, Neelam Pawar

“…Ultimately, AI is set to revolutionize pediatric eye care, improving outcomes for children worldwide while complementing the expertise of healthcare professionals.…”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…The highest tractive efficiency was observed when slip was within the 10–20% range, indicating that this slip range corresponds to the optimal operating condition. The primary findings of this study identify the appropriate slip range and provide fundamental data for developing slip control algorithms for the 4WID E-axle system. …”
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Population-based colorectal cancer risk prediction using a SHAP-enhanced LightGBM model by Guinian Du, Hui Lv, Yishan Liang, Jingyue Zhang, Qiaoling Huang, Guiming Xie, Xian Wu, Hao Zeng, Lijuan Wu, Jianbo Ye, Wentan Xie, Xia Li, Yifan Sun

“…Seven ML algorithms were systematically compared, with Light Gradient Boosting Machine (LightGBM) ultimately selected as the optimal framework. …”
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Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review by Hesameddin Akbarein, Mohammad Hussein Taaghi, Mahyar Mohebbi, Parham Soufizadeh

“…ABSTRACT In recent years, artificial intelligence (AI) has brought about a significant transformation in healthcare, streamlining manual tasks and allowing professionals to focus on critical responsibilities while AI handles complex procedures. This shift is not limited to human healthcare; it extends to veterinary medicine as well, where AI's predictive analytics and diagnostic abilities are improving standards of animal care. …”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…Existing studies consider the edges mostly equally while designing the algorithms for the unweighted contact networks, where each connection explicitly shows whether the individuals are in contact or not. …”
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Lightweight image super-resolution network based on muti-domain information enhancement by KOU Qiqi, LIU Gui, JIANG He, CHEN Liangliang, CHENG Deqiang

“…Extensive experimental comparisons and analyses with the existing advanced algorithms on the recognized benchmark datasets demonstrate that the proposed network model can achieve remarkable reconstruction results while enjoying a high trade-off between performance and efficiency.…”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. …”
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Training a Minesweeper Agent Using a Convolutional Neural Network by Wenbo Wang, Chengyou Lei

“…The results showed that in a 6 × 6 grid with four mines, the DQN model achieved an average win rate of 93.3% (standard deviation: 0.77%), while the supervised learning method achieved 91.2% (standard deviation: 0.9%), both outperforming human players and baseline algorithms and demonstrating high intelligence. …”
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Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study by Huiyu Yao, Zixin Cao, Liangfu Huang, Haojie Pan, Xiaomin Xu, Fucai Sun, Xi Ding, Wan Wu

“…Future research should focus on validating these findings in larger cohorts and exploring alternative machine-learning algorithms to improve diagnostic accuracy further.…”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…ABSTRACT In this review, we present an overview of the current state‐of‐the‐art in robotics while emphasizing stability and control aspects with pragmatic consideration over robotic manipulators. …”
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Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Despite these challenges, the hybrid model offers a promising solution for optimizing controlled environment agriculture, addressing critical challenges in modern agriculture by improving efficiency and sustainability.…”
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