A Novel Bilateral Data Fusion Approach for EMG-Driven Deep Learning in Post-Stroke Paretic Gesture Recognition by Alexey Anastasiev, Hideki Kadone, Aiki Marushima, Hiroki Watanabe, Alexander Zaboronok, Shinya Watanabe, Akira Matsumura, Kenji Suzuki, Yuji Matsumaru, Hiroyuki Nishiyama, Eiichi Ishikawa

“…This approach significantly enhanced model performance across both datasets, as evidenced by improvements in sensitivity, specificity, accuracy, and F1-score metrics. …”
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Artificial Intelligence–Enabled ECG Screening for LVSD in LBBB by Hak Seung Lee, MD, Sooyeon Lee, MD, Sora Kang, MS, Ga In Han, MS, Ah-Hyun Yoo, MS, Jong-Hwan Jang, PhD, Yong-Yeon Jo, PhD, Jeong Min Son, MD, Min Sung Lee, MD, MS, Joon-myoung Kwon, MD, MS, Kyung-Hee Kim, MD, PhD

“…Evaluating algorithms in representative clinical populations is essential.…”
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A Novel Forest Dynamic Growth Visualization Method by Incorporating Spatial Structural Parameters Based on Convolutional Neural Network by Linlong Wang, Huaiqing Zhang, Kexin Lei, Tingdong Yang, Jing Zhang, Zeyu Cui, Rurao Fu, Hongyan Yu, Baowei Zhao, Xianyin Wang

“…In addition, these visual growth models still have some space for improvement in terms of prediction accuracy and multirelational data mining. …”
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Selection of suitable reference lncRNAs for gene expression analysis in Osmanthus fragrans under abiotic stresses, hormone treatments, and metal ion treatments by Yingting Zhang, Yingting Zhang, Qingyu Yan, Hui Xia, Xiangling Zeng, Xiangling Zeng, Xiangling Zeng, Jie Yang, Jie Yang, Jie Yang, Xuan Cai, Xuan Cai, Xuan Cai, Zeqing Li, Zeqing Li, Hongguo Chen, Hongguo Chen, Hongguo Chen, Jingjing Zou, Jingjing Zou, Jingjing Zou

“…This study represents the first comprehensive evaluation of lncRNA RG stability in O. fragrans, significantly enhancing the accuracy and depth of lncRNA expression analyses in this species, contributing to advancements in plant stress resistance breeding and improving environmental adaptability.…”
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Explainable machine learning for predicting distant metastases in renal cell carcinoma patients: a population-based retrospective study by Zhao Hou, Zhao Hou, Peipei Wang, Peipei Wang, Dingyang Lv, Dingyang Lv, Huiyu Zhou, Huiyu Zhou, Zhiwei Guo, Zhiwei Guo, Jinshuai Li, Jinshuai Li, Mohan Jia, Mohan Jia, Hongyang Du, Hongyang Du, Weibing Shuang, Weibing Shuang

“…Early prediction of metastasis is crucial for developing personalized treatment plans and improving patient outcomes. This study aimed to establish and validate a clinical prediction model for distant metastasis in RCC patients.MethodsTen machine learning algorithms were employed to develop a predictive model for distant metastasis in RCC. …”
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Novel multi-omics analysis revealing metabolic heterogeneity of breast cancer cell and subsequent development of associated prognostic signature by Peng Zhang, Cuicui Li, Fen Li, Jiezhong Wu, Kunpeng Hu, He Huang

“…Understanding the metabolic heterogeneity and its interaction with the tumor microenvironment is crucial for improving prognostic predictions and therapeutic strategies. …”
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Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease by Ruijie Zhao, Yun Wang, Jiaru Wang, Zixing Wang, Ran Xiao, Ying Ming, Sirong Piao, Jinhua Wang, Lan Song, Yinghao Xu, Zhuangfei Ma, Peilin Fan, Xin Sui, Wei Song

“…Abstract Aim Timely intervention of interstitial lung disease (ILD) was promising for attenuating the lung function decline and improving clinical outcomes. The prone position HRCT is essential for early diagnosis of ILD, but limited by its high radiation exposure. …”
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Applying Neural Networks to Analyse Inflammatory, Sociodemographic, and Psychological Factors in Non-Melanoma Skin Cancer and Colon Cancer: A Statistical and Artificial Intelligenc... by Răzvan Mercuţ, Marius Eugen Ciurea, Emil Tiberius Traşcă, Mihaela Ionescu, Maria Filoftea Mercuţ, Patricia Mihaela Rădulescu, Cristina Călăraşu, Liliana Streba, Alin Gabriel Ionescu, Dumitru Rădulescu

“…Advanced neural network algorithms were employed to detect subtle patterns and interactions among these factors. …”
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Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer by Yanliang Chen, Chan Zhou, Xiaoqiao Zhang, Min Chen, Meifang Wang, Lisha Zhang, Yanhui Chen, Litao Huang, Junjun Sun, Dandan Wang, Yong Chen

“…Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets.…”
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Multi-task aquatic toxicity prediction model based on multi-level features fusion by Xin Yang, Jianqiang Sun, Bingyu Jin, Yuer Lu, Jinyan Cheng, Jiaju Jiang, Qi Zhao, Jianwei Shuai

“…Results: The experimental results indicate, first, that ATFPGT-multi outperforms ATFPGT-single on four fish datasets with AUC improvements of 9.8%, 4%, 4.8%, and 8.2%, respectively, demonstrating the superiority of multi-task learning over single-task learning. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

“…The specific models constructed for nearshore and offshore areas, as well as for the four seasons, further improves salinity retrieval accuracy, especially in nearshore regions, highlighting the effectiveness of regional and seasonal optimization strategies in complex coastal environments. …”
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Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation by Todd A. Miano, PharmD, PhD, Athena F. Zuppa, MD, MSCE, Rui Feng, PhD, Stephen Griffiths, BS, Laurel Kalman, BA, Michelle Oyster, MS, Edward Cantu, MD, MSCE, Wei Yang, PhD, Joshua M. Diamond, MD, MSCE, Jason D. Christie, MD, MSCE, Marc H. Scheetz, PharmD, MSC, Michael G.S. Shashaty, MD, MSCE

“…Results: We developed a 1-compartment base model with a fixed rate absorption constant. Covariates improving model fit were postoperative day, hematocrit, transplant type, CYP3A5 genotype, weight, and exposure to cytochrome p450 enzyme (CYP) inhibitor drugs. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Access to urban green spaces is widely regarded as an important approach to improving residents’ mental health. Exploring the impact of green space characteristics on mental health benefits can provide a theoretical basis for urban green space planning and design from the perspective of healthy city. …”
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Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…It helps in the early identification of high-risk patients and guides targeted interventions, thereby reducing the incidence of SAP and improving patient prognosis.…”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…Case studies demonstrate significant improvements in real-time monitoring, decision-making optimization, and fault response capabilities, effectively validating the proposed approach for complex systems. …”
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Utilising artificial intelligence in prehospital emergency care systems in low- and middle-income countries: a scoping review by Odhran Mallon, Odhran Mallon, Odhran Mallon, Freddy Lippert, Freddy Lippert, Willem Stassen, Marcus Eng Hock Ong, Caitlin Dolkart, Caitlin Dolkart, Thomas Krafft, Eva Pilot

“…IntroductionImprovements in prehospital emergency care have the potential to transform patient outcomes globally, but particularly within low-and middle-income countries. …”
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Construction of application platform for operational data of natural gas pipeline network by Hongtao DIAO, Weichao YU, Kaihong WANG, Huai SU, Yi ZHANG, Zhaoming YANG

“…Furthermore, deep learning algorithms and feature enhancement technologies were introduced to support the prediction of key gas volume parameters in the natural gas pipeline network. …”
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Digital Humanities & Large Language Models: Practice and Research in Semantic Retrieval of Ancient Documents by Haoxian WANG, Ziming ZHOU, Feifei DING, Chengfu WEI

“…Future efforts will be devoted to improving these issues to increase the effectiveness of the research.…”
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Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review by Ikram Bagri, Karim Tahiry, Aziz Hraiba, Achraf Touil, Ahmed Mousrij

“…Furthermore, there is a need for experimental studies to disclose the preprocessing details for datasets and the operational conditions of the machinery, thereby improving the data reproducibility. Another area that warrants further investigation is differentiation of the various types of fault information present in vibration signals obtained from bearings, as the defect information from the overall system is embedded within these signals.…”
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Development of an Artificial Neural Network-Based Image Retrieval System for Lung Disease Classification and Identification by Atul Pratap Singh, Ajeet Singh, Amit Kumar, Himanshu Agarwal, Sapna Yadav, Mohit Gupta

“…The CNN architecture is then meticulously constructed, with attention to layer configurations, activation functions, and optimization algorithms to facilitate effective learning and classification. …”
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