Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…Eligible articles were screened and categorized based on application domains, AI models used, datasets, and reported outcomes. …”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…In this context, “in silico” describes scientific studies performed using computer algorithms, simulations, or digital models to analyze biological, chemical, or physical processes without the need for laboratory (in vitro) or live (in vivo) experiments. …”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…Background/Objectives: Artificial Intelligence (AI) in healthcare employs advanced algorithms to analyze complex and large-scale datasets, mimicking aspects of human cognition. …”
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Integrating digital and narrative medicine in modern healthcare: a systematic review by Efthymia Efthymiou

“…The increasing integration of digital technologies in healthcare, such as electronic health records, telemedicine, and diagnostic algorithms, improved efficiency but raised concerns about the depersonalization of care. …”
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Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
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Optimization of Coulomb energies in gigantic configurational spaces of multi-element ionic crystals by Konstantin Köster, Tobias Binninger, Payam Kaghazchi

“…Coulomb energies of possible configurations generally show a satisfactory correlation to computed energies at higher levels of theory and thus allow to screen for minimum-energy structures. Employing an expansion into a binary optimization problem, we obtain an efficient Coulomb energy optimizer using Monte Carlo and Genetic Algorithms. …”
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Identification of podocyte molecular markers in diabetic kidney disease via single-cell RNA sequencing and machine learning. by Hailin Li, Quhuan Li, Zuyan Fan, Yue Shen, Jiao Li, Fengxia Zhang

“…Multiple machine-learning algorithms were used to screen and construct diagnostic models to identify hub differentially expressed podocyte marker genes (DE-podos), revealing ARHGEF26 as a significantly downregulated marker in DKD. …”
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Identifying potential three key targets gene for septic shock in children using bioinformatics and machine learning methods by Wei Guo, Hao Chen, Feng Wang, Yingjiao Chi, Wei Zhang, Shan Wang, Kezhu Chen, Hong Chen

“…Three kinds of machine learning models were established, and the candidate genes were screened by intersection to obtain the core genes with diagnostic value. …”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

“…Partial least squares regression (PLSR) models for 17 phenolic components and moisture content were screened using different preprocessing methods, identifying three parameters suitable for rapid quantification: eupatilin, jaceosidin, and moisture. …”
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Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…DNA methylation data from 696 newly diagnosed and 194 relapsed pediatric AML patients were analyzed. Feature selection algorithms, including Boruta, least absolute shrinkage and selection operator, light gradient boosting machine, and Monte Carlo feature selection, were employed to screen and rank methylation sites strongly correlated with AML recurrence. …”
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Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis by Chuang Yang, Yi-Hang Liu, Hai-Kuo Zheng

“…This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Also, the most applied machine learning algorithms are Linear Regression (LR), Random Forest (RF), and Gradient Boosting Trees (GBT) whereas the most applied deep learning algorithms are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM). …”
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Intelligent design and synthesis of energy catalytic materials by Linkai Han, Zhonghua Xiang

“…We summarize the sources of data collection, the intelligent algorithms commonly used to build ML models, and the laboratory modules for the intelligent synthesis of materials. …”
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Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

“…ISR scores were compared across brain cell types, and differentially expressed genes in microglia were further screened using Lasso regression and random forest algorithms. …”
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Disentangling High-Paced Alternating I/O in Gaze-Based Interaction by Yulia G. Shevtsova, Artem S. Yashin, Sergei L. Shishkin, Anatoly N. Vasilyev

“…When playing the game, 15 volunteers selected screen objects using a 500 ms dwell time without additional actions for intention confirmation. …”
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A scoping review on metrics to quantify reproducibility: a multitude of questions leads to a multitude of metrics by Rachel Heyard, Samuel Pawel, Joris Frese, Bernhard Voelkl, Hanno Würbel, Sarah McCann, Leonhard Held, Kimberley E. Wever, Helena Hartmann, Louise Townsin, Stephanie Zellers

“…The metrics were characterized based on type (formulas and/or statistical models, frameworks, graphical representations, studies and questionnaires, algorithms), input required and appropriate application scenarios. …”
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Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review by Émile Lemoine, Joel Neves Briard, Bastien Rioux, Oumayma Gharbi, Renata Podbielski, Bénédicte Nauche, Denahin Toffa, Mark Keezer, Frédéric Lesage, Dang K. Nguyen, Elie Bou Assi

“…Significance: We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.…”
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FGFR2 identified as a NETs-associated biomarker and therapeutic target in diabetic foot ulcers by Linrui Dai, Shunli Rui, Mengling Yang, Shiyan Yu, Qingqing Chen, Hongyan Wang, Bo Deng, Liling Deng, Wei Hao, Xiaohua Wu, David G. Armstrong, Zhidong Cao, Xiaodong Duan, Wuquan Deng

“…LASSO logistic regression and Random Forest algorithms were applied to the NETDEGs to select key feature genes. …”
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IKZF1 as a potential therapeutic target for dendritic cell-mediated immunotherapy in IgA nephropathy by Fei Peng, Chunjia Sheng, Jiayi He, Yena Zhou, Yilun Qu, Shuwei Duan, Yinghua Zhao, Jikai Xia, Jie Wu, Guangyan Cai, Lingling Wu, Chuyue Zhang, Xiangmei Chen

“…Receiver operating characteristic (ROC) curve analysis and machine learning algorithms were employed to screen for DC-related diagnostic biomarkers from the dataset. …”
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