Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…This algorithm aims to create a prediction map of habitats dominated by Quercus cerris, which is also known as the relevancy map.Through the utilisation of the Natural Numerical Network, a training accuracy of 95.24% was achieved. …”
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A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs by Xiaohao Mao, Yu Huang, Ye Jin, Lun Wang, Xuanzhong Chen, Honghong Liu, Xinglin Yang, Haopeng Xu, Xiaodong Luan, Ying Xiao, Siqin Feng, Jiahao Zhu, Xuegong Zhang, Rui Jiang, Shuyang Zhang, Ting Chen

“…In 1936 test cases, PhenoBrain achieved an average predicted top-3 recall of 0.513 and a top-10 recall of 0.654, surpassing 13 leading prediction methods. …”
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External particle mixing influences hygroscopicity in a sub-urban area by S. Deshmukh, L. Poulain, B. Wehner, S. Henning, J.-E. Petit, P. Fombelle, P. Fombelle, O. Favez, H. Herrmann, M. Pöhlker, M. Pöhlker

“…These emphasise the large effect of external particle mixing and its influence on predicting hygroscopicity. The ZSR approach proves to be unreliable in predicting the wide growth distribution of externally mixed particles. …”
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Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend by V. Capozzi, F. Serrapica, A. Rocco, C. Annella, C. Annella, G. Budillon

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An EEG-based framework for automated discrimination of conversion to Alzheimer’s disease in patients with amnestic mild cognitive impairment: an 18-month longitudinal study by Yingfeng Ge, Jianan Yin, Caie Chen, Shuo Yang, Yuduan Han, Chonglong Ding, Jiaming Zheng, Yifan Zheng, Jinxin Zhang

“…The performance of each model was assessed using 10-fold cross-validation and evaluated in terms of accuracy (ACC), area under the curve (AUC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), and F1-score.ResultsCompared to SMCI patients, PMCI patients exhibit a trend of “high to low” frequency shift, decreased complexity, and a disconnection phenomenon in EEG signals. …”
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Structural engineering of stabilized, expanded epitope nanoparticle vaccines for HPV by Michaela Helble, Michaela Helble, Xizhou Zhu, Pratik S. Bhojnagarwala, Kevin Liaw, Yangcheng Gao, Amber Kim, Kelly Bayruns, Madison E. McCanna, Joyce Park, Kylie M. Konrath, Kylie M. Konrath, Sam Garfinkle, Sam Garfinkle, Taylor Brysgel, David B. Weiner, David B. Weiner, Daniel W. Kulp, Daniel W. Kulp

“…We developed a platform, making use of structural prediction algorithms such as AlphaFold2, to design stabilized, more full-length antigens of relevant HPV proteins and then display them on nanoparticles. …”
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Age‐related longitudinal change in cardiac structure and function in adults at increased cardiovascular risk by Fei Fei Gong, Jennifer M. Coller, Michele McGrady, Umberto Boffa, Louise Shiel, Danny Liew, Simon Stewart, Alice J. Owen, Henry Krum, Christopher M. Reid, David L. Prior, Duncan J. Campbell

“…We examined age‐associated longitudinal change in cardiac structure and function, and their prediction by age and cardiovascular disease (CVD) risk factors, in a community‐based cohort aged ≥60 years at increased CVD risk but without HF. …”
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Right ventricular mechanical pattern in patients undergoing mitral valve surgery: a predictor of post‐operative dysfunction? by Márton Tokodi, Endre Németh, Bálint K. Lakatos, Erika Kispál, Zoltán Tősér, Levente Staub, Kristóf Rácz, Ádám Soltész, Szabolcs Szigeti, Tamás Varga, János Gál, Béla Merkely, Attila Kovács

“…Advanced indices of RV mechanics are associated with invasively measured parameters of RV contractility and may predict post‐operative RVD.…”
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Research on Monitoring Methods for the Appropriate Rice Harvest Period Based on Multispectral Remote Sensing by Chen Cong, Cao Guangqiao, Li Yibai, Liu Dong, Ma Bin, Zhang Jinlong, Li Liang, Hu Jianping

“…In single-band inversion models, the regression effect at 735 nm was relatively good in the BP neural network model, with the highest determination coefficients of spectral reflectance and thousand-grain weight of both rich varieties and the smallest RMSE of prediction results. In combined-band inversion models, the regression effects at 550 + 660+735 nm and 660 + 735+790 nm were the best in the SVM and thousand-grain weight inversion models.…”
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Prognostic value of neutrophil-to-lymphocyte ratio dynamics in patients with septic acute kidney injury: a cohort study by Wei Wei, Caihong Liu, Guojiao Song, Letian Yang, Jian Li, Bo Wang, Ting Yin, Yingying Yang, Liang Ma, Ling Zhang, Ping Fu, Yuliang Zhao

“…The relationship between the ΔNLR and mortality was evaluated by Kaplan–Meier curves, Cox proportional hazards, and cubic spline analyses. The prediction values were compared by area under the receiver-operating characteristic curve (AUROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses.Results Of the 413 participants, the mean age was 63 ± 17 years, and 134 were female (32.4%). …”
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Use of supervised and unsupervised approaches to make zonal application maps for variable-rate application of crop growth regulators in commercial cotton fields by Maria C. da S. Andrea, Cristiano F. de Oliveira, Fabrícia C. M. Mota, Rafael C. dos Santos, Edilson F. Rodrigues Junior, Lucas M. Bianchi, Rodrigo S. de Oliveira, Caio M. de Gouveia, Victor G. S. Barbosa, Marco A. Bispo E Silva

“…This led to variable compatibility between SUF maps, which utilized the model predictions, and the UF maps, which were based on the real field data. …”
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Influence of Stress Sensitivity on Water-Gas Flow in Carbonate Rocks by Shuaishi Fu, Lianjin Zhang, Yingwen Li, Xuemei Lan, Roohollah Askari, Junjie Wang, Wen Wen, Xinze Li, Shaobin Cai, Ke Wang, Jie Liu, Yushu Wang, Yongfei Yang

“…Due to their strong heterogeneity, it is of great significance to study core seepage capacity and gas-water two-phase flow of reservoirs with various pore structures under different stresses for productivity prediction, gas reservoir development, and reservoir protection. …”
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MicroRNA-26b inhibits cardiac remodeling after myocardial infarction by targeting ring finger protein 6 expression by Chun-Mei Tang, Qiang Su, Hai-Xia Zhao, He-Huan Sui, Jing Liang, Li-Sha Zhu, Si-Yun Yang, Tao Liu

“…Consequently, miR-26b was identified to target RNF6 using dual-luciferase reporter assay and bioinformatics prediction. Furthermore, rats injected with a lentiviral vector expressing miR-26b mimic and/or RNF6 were used to evaluate the role of miR-26b and RNF6 in regulating cardiac function, infarct size, and cardiomyocyte apoptosis. …”
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Causal associations of ambient particulate matter 10 and Alzheimer’s disease: result from a two-sample multivariable Mendelian randomization study by Zehan Huang, Guodong He, Shuo Sun, Yingqing Feng, Yuqing Huang

“…This study provided evidence of genetic prediction of a causal relationship between PM10 and the risk of AD, suggesting that air pollution control may have significant implications for the prevention of AD.…”
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The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses by Liu Jun, Hongguo Li, Yu Mao, Lan Hu, Dan Wu

“…The inclusion of BI in the models improved the overall predictive performance, highlighting its positive impact on SI prediction.ConclusionThe study employed various statistical methodologies to demonstrate a significant negative correlation between ADL and SI, a finding further corroborated by machine learning algorithms. …”
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Use of Blood Lipid Indicators as a Screening Tool of Insulin Resistance among Individuals in Low-Income Country Sides of China: A Multiethnic Region Study by Yi-Zhong Yan, Jia-Ning Fan, Jia-Ming Liu, Yun-hua Hu, Jiao-Long Ma, Jia He, Heng Guo, Xiang-hui Zhang, Xin-ping Wang, Shu-gang Li, Shu-Xia Guo

“…The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value, and the nomogram was utilized to analyze the predictive value. The size of the area under the curve (AUC) reflected the accuracy of screening and prediction. …”
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Retrospective cohort study on diseases and risk factors associated with death in hospitalized neonatal foals by Donatienne L. Castelain, Alexander Dufourni, Mathilde L. Pas, Jade Bokma, Eva deBruijn, Ellen Paulussen, Laurence Lefère, Gunther vanLoon, Bart Pardon

“…Abstract Background The care of sick neonatal foals is labor‐intensive and costly. Prediction of risk of death upon admission is often difficult but might support decision‐making. …”
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Rapid identification of high-temperature Daqu Baijiu with the same aroma type by UV-VIS sensor of HBT combined with Zn2+ by Yanmei Zhu, Yuanyuan Su, Yipeng Cang, Hengye Chen, Wanjun Long, Wei Lan, Xue Jiang, Haiyan Fu

“…Twelve kinds of Maillard reaction products such as tetramethylpyrazine, 2,6-dimethylpyrazine, and furfural in Baijiu were predicted successfully, and the deviation between the real value and the predicted value was less than 1.8746% ± 1.4515%. …”
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Pharmacogenomics predictors of aromatic antiepileptic drugs-induced SCARs in the Iraqi patients by Ali Fadhel Ahmed, Dzul Azri Mohamed Noor, Majeed Arsheed Sabbah, Nur Fadhlina Musa, Nur Aizati Athirah Daud

“…These findings could facilitate personalized medicine approaches, aiding in better prediction and prevention of SCARs in AED therapy.…”
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Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model by Xing Tu, Zixing Zou, Jiahui Li, Simiao Zeng, Zhengchao Luo, Gen Li, Yuanxu Gao, Kang Zhang, Jing Ni

“…Subsequently, these target candidates were validated using molecular simulations (molecular docking, absorption, distribution, metabolism, excretion, and toxicity [ADMET] prediction, and molecular dynamics simulations) and biological experiments (Western blotting and fluorescence staining) in vitro and in vivo. …”
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