Linking Immunological Parameters and Recovery of Patient’s Motor and Cognitive Functions In The Acute Period of Ischemic Stroke by A. M. Tynterova, N. N. Shusharina, A. M. Golubev, E. M. Moiseeva, L. S. Litvinova

“…To evaluate the relationship between immunological parameters and functional outcome in patients with varying severity of ischemic stroke based on statistical methodology.Materials and methods. …”
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Prediction of depressive disorder using machine learning approaches: findings from the NHANES by Thien Vu, Research Dawadi, Masaki Yamamoto, Jie Ting Tay, Naoki Watanabe, Yuki Kuriya, Ai Oya, Phap Ngoc Hoang Tran, Michihiro Araki

“…Traditional analysis methods often suffer from subjectivity and may not capture complex, non-linear relationships between risk factors. Machine learning (ML) offers a data-driven approach to predict and diagnose depression more accurately by analyzing large and complex datasets. …”
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Exploring machine learning classification for community based health insurance enrollment in Ethiopia by Seyifemickael Amare Yilema, Seyifemickael Amare Yilema, Yegnanew A. Shiferaw, Yikeber Abebaw Moyehodie, Setegn Muche Fenta, Denekew Bitew Belay, Denekew Bitew Belay, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Teshager Zerihun Nigussie, Ding-Geng Chen, Ding-Geng Chen

“…The CBHI were predicted using seven machine learning models: linear discriminant analysis (LDA), support vector machine with radial basis function (SVM), k-nearest neighbors (KNN), classification and regression tree (CART), and random forest (RF). …”
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Ganoderma Disease in Oil Palm Trees Using Hyperspectral Imaging and Machine Learning by Chee Seng Kwang, Siti Fatimah Abdul Razak, Sumendra Yogarayan, M. Z. Adli Zahisham, Tze Huey Tam, M. K. Anuar Mohd Noor, Haryati Abidin

“…SVM with radial basis function (RBF) and polynomial kernels show the second highest performance, attaining 91.67% accuracy, 83.33% sensitivity, and 100% specificity. …”
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Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning by Shuyan Zhang, Jingtan Li, Lin Shen, Zhonghao Zhao, Minjun Lee, Kun Qian, Naidi Sun, Bin Hu

“…Yet, existing methods rarely achieve effective recovery of functional images. In this study, we propose Mask-enhanced U-net (MeU-net) for recovering sparsely sampled PAM structural and functional images. …”
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Temperature-dependent plasticity in organic synaptic transistors for adaptive learning and data encryption by Yu Gao, Xue-Er Han, Xu Gao, Fei-Le Xue, Jian-Ru Chen, Ya-Nan Zhong, Jian-Long Xu, Sui-Dong Wang

“…By leveraging these thermal responses, we establish a temperature-dependent physical unclonable function (PUF) capable of multi-level logic encoding and self-annihilating data storage. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The results indicated that the accuracies of neural network models, including Convolutional Neural Network, Long Short-Term Memory, Radial Basis Function (RBF) neural network, and Extreme Learning Machine, exceeded 84.24 %, with Kappa coefficients greater than 0.79. …”
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Sex differences in psychosocial functioning and neurocognition in bipolar disorder: a systematic review and meta-analysis by Maria Serra-Navarro, Derek Clougher, Vincenzo Oliva, Clàudia Valenzuela-Pascual, Michele De Prisco, María Florencia Forte, Marina Garriga, Brisa Solé, Jose Sánchez-Moreno, Norma Verdolini, Giulia Menculini, Alfonso Tortorella, Miquel Bernardo, J. Antoni Ramos-Quiroga, Anabel Martinez-Aran, Eduard Vieta, Silvia Amoretti, Carla Torrent

“… Abstract Introduction Impairment in both psychosocial functioning and neurocognition (NC) performance is present in bipolar disorder (BD) yet the role of sex differences in these deficits remains unclear. …”
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Pose measurement method for coal mine drilling robot based on deep learning by Jiangnan LUO, Jianping LI, Hongxiang JIANG, Deyi ZHANG

“…Next, a generative adversarial network was integrated into the PointNet++ to capture more complex and detailed point cloud features. A focal loss function was employed to enhance the model's focus on the drill head and gripper, and Bayesian parameter optimization was used for hyperparameter tuning. …”
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Deep learning-based diffusion MRI tractography: Integrating spatial and anatomical information by Yiqiong Yang, Yitian Yuan, Baoxing Ren, Ye Wu, Yanqiu Feng, Xinyuan Zhang

“…Additionally, we employ a weighted loss function to address fiber class imbalance encountered during training. …”
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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

“…To explore the relative merits of these two approaches, we have developed a two-layered machine-learning reconstruction model MEMLM (Multi Ensemble Machine Learning Model). …”
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Fault diagnosis and inference of hoist main bearing based on transfer learning and ontology by Fei DONG, Di ZHANG, Kunpeng GE, Junjie CHEN, Xinyue XU

“…To overcome the challenges still faced by data-driven hoist main bearing fault diagnosis methods, including data imbalance due to a lack of fault samples under real operating conditions, diagnostic performance degradation of fault diagnosis models caused by significant differences in data sample distribution under varying conditions, single fault diagnosis function, and a lack of reasoning analysis and localization for the causes of hoist main bearing system failures, a new fault diagnosis and reasoning method for hoist main bearing systems is studied, which includes two aspects: ① Bearing fault diagnosis based on convolutional neural network transfer learning and domain adaptation. …”
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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

“…This study presents a novel dual approach for diabetes risk prediction in women, combining machine learning classification with fractional-order physiological modeling. …”
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Impaired cognitive function and decreased monoamine neurotransmitters in the DNAJC12 gene knockout mouse model by Shunan Wang, Ming Shen, Bo Pang, Bo Zhou, Yuan Yuan, Mei Lu, Xiangling Deng, Min Yang, Shufang Liu, Qiong Wang, Mei Xue, Qisheng Xia, Zhixin Zhang

“…The knockout mice exhibit hyperphenylalaninemia, impaired cognitive function, and decreased monoamine neurotransmitters. …”
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Long COVID in Elderly COPD Patients: Clinical Features, Pulmonary Function Decline, and Proteomic Insights by Li S, Zhao H, Zhang M, Yuan T, Chai D, Shen Z, Qin C, Li Y, Pan M

“…Patients completed questionnaires, pulmonary function tests, chest CT, routine laboratory tests, and blood proteomic analysis.Results: Long-COVID patients had a longer course of COPD (> 5 years, 76.8% vs 52.4%) and duration of SARS-CoV-2 infection (10.0 days vs 7.0 days) (All P < 0.05), higher symptom burden, worse pulmonary ventilation function and a more rapid decrease in DLCO (All P < 0.05). …”
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Ferroportin 1 depletion in neural stem cells promotes hippocampal neurogenesis and cognitive function in mice by Yiqian Ding, Shanshan Yao, Shuxin Guo, Wei Meng, Jie Li, Fudi Wang, Jianhua Zhang, Yan-Zhong Chang, Guofen Gao

“…In the adult brain, newborn granule cells continuously integrate into the hippocampal circuits, and fine-tuning the regulation of this process is crucial for improving hippocampal function. Iron is an essential element for the development and functionality of the brain. …”
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Decoding methane concentration in Alberta oil sands: A machine learning exploration by Liubov Sysoeva, Ilhem Bouderbala, Miles H. Kent, Esha Saha, B.A. Zambrano-Luna, Russell Milne, Hao Wang

“…We additionally use Shapley values to find that O3’s relationship with methane concentration is consistently concave, while that of NOX changes from linear increase to a saturation function with increasing distance from OSTPs. This paper serves as a guide for building machine learning-driven models to estimate methane concentration in Alberta’s oil sands, or similar regions with methane-producing extractive industries.…”
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Probiotic potential of Phocaeicola coprocola in modulating learning and memory behaviors in the honeybee model by Mengqi Xu, Mengqi Xu, Xiaohan Zhang, Xiaohan Zhang, Xi Luo, Guanzhou Zhou, Guanzhou Zhou, Nana Zhang, Xiaoyan Chi, Xiaoyan Chi, Rongrong Ren, Lihua Peng, Gang Sun, Yunsheng Yang, Yunsheng Yang

“…IntroductionGut microbial therapy has emerged as a prominent research topic for brain function and disorders. The depletion of Phocaeicola coprocola has been reported in various brain-related conditions, suggesting its possible neuroprotective and cognitive benefits. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. …”
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Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT by Mateusz Koziński, Doruk Oner, Jakub Gwizdała, Catherine Beigelman-Aubry, Pascal Fua, Angela Koutsokera, Alessio Casutt, Argyro Vraka, Michele De Palma, John-David Aubert, Horst Bischof, Christophe von Garnier, Sahand Jamal Rahi, Martin Urschler, Nahal Mansouri

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