Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers by Mariah Batool, Oluwafemi Sanumi, Jasna Jankovic

“…This review begins by explaining the fundamental concepts of artificial intelligence and introducing commonly used artificial intelligence-based algorithms in a simplified and clearly comprehensible way, establishing a foundational knowledge base for further discussion. …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems.…”
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Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

“…The results indicate that NP-SNN provides a robust Sci-ML framework that can make accurate predictions across diverse scientific molecular applications. …”
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Correlation Between Clinical Indicators and Liver Pathology in Children with Chronic Hepatitis B by Chenyang Huang, Ying Lu, Ziwei Wang, Qiyu Jiang, Yi Dong, Lili Cao, Jianguo Yan, Zhiqiang Xu, Fuchuan Wang, Yinjie Gao, Junliang Fu, Min Zhang, Fu-Sheng Wang

“…Our findings highlight the value of integrating age and key biochemical markers into non-invasive diagnostic algorithms for the early detection and management of liver pathology in children.…”
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The 3-level Wells score combined with D-dimer can accurately diagnose acute pulmonary embolism in hospitalized patients with acute exacerbation of COPD: A multicentre cohort study by Xiaojing Jiao, Yixiao zhang, Tuguang Kuang, Juanni Gong, Yadong Yuan, Guohua Zhen, Jifeng Li, Suqiao Yang, Jianguo He, Yuanhua Yang

“…We aim to investigate the predictive accuracy of two clinical scoring systems combined with D-dimer for APE in patients with AECOPD. …”
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Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning by Si Xie, Mo Wu, Yu Shang, Wenbin Tuo, Jun Wang, Qinzhen Cai, Chunhui Yuan, Cong Yao, Yun Xiang

“…Clinical data were selected through Lasso regression analysis, followed by the application of eight machine learning algorithms to develop early warning model. The accuracy of the model was assessed using validation and prospective cohort. …”
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In-Silico discovery of novel cephalosporin antibiotic conformers via ligand-based pharmacophore modelling and de novo molecular design by Rayhan Chowdhury, Samia Akter Saima, Md. Al Amin, Md. Kawsar Habib, Ramisa Binti Mohiuddin, Ali Mohamod Wasaf Hasan, Roksana Khanam, Shahin Mahmud

“…This research aims to predict new compounds using ligand-based pharmacophore models while optimizing existing drugs. …”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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In Vitro Oral Cavity Permeability Assessment to Enable Simulation of Drug Absorption by Pankaj Dwivedi, Priyata Kalra, Haiying Zhou, Khondoker Alam, Eleftheria Tsakalozou, Manar Al-Ghabeish, Megan Kelchen, Giovanni M. Pauletti

“…<b>Conclusions</b>: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. …”
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Estimation of the water content of needles under stress by Erannis jacobsoni Djak. via Sentinel-2 satellite remote sensing by Jiaze Guo, Xiaojun Huang, Xiaojun Huang, Xiaojun Huang, Debao Zhou, Junsheng Zhang, Gang Bao, Gang Bao, Siqin Tong, Siqin Tong, Yuhai Bao, Yuhai Bao, Dashzebeg Ganbat, Dorjsuren Altanchimeg, Davaadorj Enkhnasan, Mungunkhuyag Ariunaa

“…Needle leaf water content exhibits a clear response to these changes and is highly sensitive in reflecting the degree of tree damage.MethodsIn this work, we combine vegetation indices with machine learning algorithms to estimate the water content of needles at a large scale. …”
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Comprehensive analysis of phagocytosis regulatory genes in bladder cancer: implications for prognosis and immunotherapy by Xueming Ma, Xueming Ma, Xueming Ma, Dongnuan Yao, Dongnuan Yao, Dongnuan Yao, Weitao Yu, Weitao Yu, Weitao Yu, Gongping Wu, Gongping Wu, Gongping Wu, Chengwei Fan, Chengwei Fan, Chengwei Fan, Junqiang Tian, Junqiang Tian, Junqiang Tian

“…The constructed prognostic model showed excellent predictive performance, and the areas under the curves of survival rates at different times were all high in both the training set and the test set. …”
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Deciphering the impact of intra-tumoral bacterial infiltration on multi-omics profiles in low-grade gliomas by Wenshu Li, Zixiang Zhu, Zixiang Zhu, Longyuan Li, Xin Wu, Jiaxuan Li, Yi Zhou, Lingwen Gu, Pranathi Vittal, Zhouqing Chen, Zhong Wang, Lingchuan Guo

“…For the TCGA samples, utilizing advanced machine learning algorithms, this study identified distinct patterns of bacterial infiltration within the LGG population and constructed a prognostically relevant intra-tumoral bacteria risk model (PRIBR Index). …”
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DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure by Wenwu Tang, Wenwu Tang, Zhixin Wang, Xinzhu Yuan, Liping Chen, Haiyang Guo, Zhirui Qi, Ying Zhang, Xisheng Xie

“…In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.ResultsTotally 23 candidate genes were screened out by overlapping 673 differentially expressed genes (DEGs) and 147 key module genes, of which four hub genes (DEPDC1B, CDCA2, APOBEC3B and TYMS) were obtained by two machine learning algorithms. Through GSEA analysis, it was found that the four genes were closely related to ribosome, cell cycle, ubiquitin-mediated proteolysis. …”
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Epidemiological, molecular, and evolutionary characteristics of G1P[8] rotavirus in China on the eve of RotaTeq application by Rui Peng, Rui Peng, Mengxuan Wang, Saleha Shahar, Guangping Xiong, Qing Zhang, Lili Pang, Hong Wang, Xiangyu Kong, Dandi Li, Zhaojun Duan

“…Neutralizing epitope, amino acid selection pressure, and evolution dynamics analyses on VP7 and VP4 were performed using BioEdit v.7.0.9.0 and PyMOL v.2.5.2, four algorithms (MEME, SLAC, FEL, and FUBAR) in the Datamonkey online software, and the MCMC model in BEAST v. 1.10.4, respectively. …”
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Optimal vaccination model of airborne infection under variable humidity and demographic heterogeneity for hybrid fractional operator technique by Saima Rashid, Ilyas Ali, Nida Fatima, Tehreem Fatima, Fekadu Tesgera Agam, Sayed K. Elagan

“…Our system’s best-fit parameter settings were detected using the Markov Chain Monte Carlo (M-C-M-C) technique with influenza information collected in Spain. We predict a basic reproduction number of 1.3645 (96% C.I: (1.3644, 1.3646)). …”
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At-Home Evaluation of Both Wearable and Touchless Digital Health Technologies for Measuring Nocturnal Scratching in Atopic Dermatitis: Analytical Validation Study by Stefan Avey, Mark Morris, Davit Sargsyan, Molly V Lucas, Andrea O'Brisky, Kenneth Mosca, Andrew Elias, Nicholas Fountoulakis, Mehdi Boukhechba, Xuen Hoong Kok, Saiyam Jain, Mehrnoosh Oghbaie, Nikolay V Manyakov, Miao Wang, Zuleima Aguilar, Lynn Yieh

“…ObjectiveIn this study, we present the analytical validation of 2 DHTs: the GENEActiv wristband with Philips sleep and scratch algorithms (“Philips”) and the Emerald radio frequency touchless sensor (“Emerald”) to measure nocturnal scratching in adults with AD. …”
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Bioinformatics&amp;#x2011;Based Analysis Reveals Diagnostic Biomarkers and Immune Landscape in Atopic Dermatitis by Yang M, Zhang X, Zhou C, Du Y, Zhou M, Zhang W

“…Least Absolute Shrinkage and Selection Operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to screen hub genes. Immune cell infiltration was evaluated using CIBERSORT. …”
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The underlying molecular mechanisms and biomarkers of Hip fracture combined with deep vein thrombosis based on self sequencing bioinformatics analysis by Guanghua Shi, Xiaocui Shi, Meng Zhang, Rui Cheng, Mengqing Hu, Yu Zhao, Shimei Li, Xiuxiu Li, Haiyun Ma, Pengcui Li

“…Feature genes were further refined by intersecting results from three machine learning algorithms and constructing an artificial neural network (ANN). …”
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Identifying mating events of group-housed broiler breeders via bio-inspired deep learning models by Venkat U.C. Bodempudi, Guoming Li, J. Hunter Mason, Jeanna L. Wilson, Tianming Liu, Khaled M. Rasheed

“…The DLM framework included a bird detection model, data filtering algorithms based on mating duration, and logic frameworks for mating identification based on bird count changes. …”
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Aneuploidy screening in women of advanced age in the public healthcare setting of a low- to middle- income country – an observational cohort study by L Geerts, N Du Toit, M Schoeman

“…In the SA public sector, DS screening and confirmatory genetic testing are fully state subsidised for women of advanced maternal age (AMA) but, owing to the low positive predictive value of AMA-based screening, ultrasound-based screening is also offered. …”
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