Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory by Mumtaz Ali, Jesu Vedha Nayahi, Erfan Abdi, Mohammad Ali Ghorbani, Farzan Mohajeri, Aitazaz Ahsan Farooque, Salman Alamery

“…The main purpose of this investigation was to forecast the daily ETo trends at Melbourne and Sydney stations in Australia, where several cutting-edge machine learning methodologies were employed. The modeling approach encompassed the implementation of Neural Network (NN), Deep Learning (DL), Recurrent Neural Networks (RNN), RNN based Long Short-Term Memory (RNN-LSTM), and Convolutional Neural Network based LSTM (CNN-LSTM) to forecast daily ETo using historical meteorology data. …”
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Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (<i>Annona squamosa</i> L.) by Xiangtai Jiang, Lutao Gao, Xingang Xu, Wenbiao Wu, Guijun Yang, Yang Meng, Haikuan Feng, Yafeng Li, Hanyu Xue, Tianen Chen

“…This study uses an ensemble learning technique based on multiple machine learning algorithms to effectively and precisely monitor the leaf nitrogen content in the tree canopy using multispectral canopy footage of custard apple trees taken via Unmanned Aerial Vehicle (UAV) across different growth phases. …”
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Determining the status of tertiary lymphoid structures in invasive pulmonary adenocarcinoma based on chest CT radiomic features by Ye Yu, Tianshu Yang, Pengfei Ma, Yan Zeng, Yongming Dai, Yicheng Fu, Aie Liu, Ying Zhang, Guanglei Zhuang, Yan Zhou, Huawei Wu

“…Radiomic features were extracted, and support vector machine (SVM) were implemented to predict the status of TLSs. …”
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Gestational exposure to environmental chemical mixtures and cognitive abilities in children: A pooled analysis of two North American birth cohorts by Jagadeesh Puvvula, Wei-Ting Hwang, Lawrence McCandless, Changchun Xie, Joseph M. Braun, Ann M. Vuong, Youssef Oulhote, Enrique F. Schisterman, Russell T. Shinohara, Linda Booij, Maryse F. Bouchard, Kristin Linn, Michael M. Borghese, Jean R. Seguin, Angelika Zidek, Christine Till, William Fraser, Kimberly Yolton, Kim M. Cecil, Jillian Ashley-Martin, Tye E. Arbuckle, Bruce Lanphear, Aimin Chen

“…We assessed linear associations using quantile g-computation and non-linear associations using Bayesian Kernel Machine Regression (BKMR) methods, adjusted for covariates. …”
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ANN-based two hidden layers computational procedure for analysis of heat transport dynamics in polymer-based trihybrid Carreau nanofluid flow over needle geometry by Adil Darvesh, Fethi Mohamed Maiz, Basma Souayeh, Luis Jaime Collantes Santisteban, Hakim AL. Garalleh, Afnan Al Agha, Lucerito Katherine Ortiz García, Nicole Anarella Sánchez-Miranda

“…Their advantages in handling nonlinearities and modeling high-dimensional data through integrating physical laws make them far superior to simpler machine learning and other traditional techniques, despite requiring greater data and computational resources. …”
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5G Networks Security Mitigation Model: An ANN-ISM Hybrid Approach by Rafiq Ahmad Khan, Habib Ullah Khan, Hathal Salamah Alwageed, Hussein Al Hashimi, Ismail Keshta

“…The proposed model includes state-of-the-art machine learning with traditional information security paradigms to offer an integrated solution to the emerging complex security issues related to 5G. …”
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Association between estimated glucose disposal rate and cardiovascular diseases in patients with diabetes or prediabetes: a cross-sectional study by Jinhao Liao, Linjie Wang, Lian Duan, Fengying Gong, Huijuan Zhu, Hui Pan, Hongbo Yang

“…Methods 10,690 respondents with diabetes and prediabetes from the NHANES 1999–2016 were enrolled in the study. Three machine learning methods (SVM-RFE, XGBoost, and Boruta algorithms) were employed to select the most critical variables. …”
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Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.) by Zhu Yang, Zhu Yang, Wenjie Kan, Wenjie Kan, Ziqi Wang, Caiguo Tang, Yuan Cheng, Yuan Cheng, Dacheng Wang, Dacheng Wang, Yameng Gao, Lifang Wu, Lifang Wu

“…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …”
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Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA by Po-Ku Chen, Joung-Liang Lan, Yi-Ming Chen, Hsin-Hua Chen, Shih-Hsin Chang, Chia-Min Chung, Nurul H. Rutt, Ti-Myen Tan, Raja Nurashirin Raja Mamat, Nur Diana Anuar, Jonathan M. Blackburn, Der-Yuan Chen

“…The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median=0.024 μg/ml) compared with ADAb-negative patients (median=6.38 μg/ml, p<0.001). …”
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Association between exposure to perfluoroalkyl and polyfluoroalkyl substances with estimated glomerular filtration rate: Mediating role of serum albumin by Hua Fang, Huajing Chang, Danjing Chen, Wenxin Qiu, Jiangwang Fang, Yunli Wu, Xian-E. Peng

“…Associations between perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonate (PFHxS), and perfluorononanoic acid (PFNA) with eGFR and the risk of decreased renal function (eGFR < 90 vs. eGFR ≥ 90) using linear and logistic regression, weighted quantile sum (WQS) regression, Bayesian kernel machine regression (BKMR), and restricted cubic spline (RCS) analyses. …”
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The Epidemiological Characteristics of Coronavirus Disease (COVID-19) in Halabja Province/Kurdistan –Iraq by Osama Hamid Shareef, Othman Abdulrahman Mohammed, Dashty Aziz Ghafor, Ari Shareef Ali, Hardi Rafat Baqi, Ali Aziz Ali, Aryan Mahmood Faraj, Syamand Ahmed Qadir, Ali Muhi Aldeen Omar Aljabary

“…Samples were obtained nasopharyngeal using a sterilized swab following WHO guidelines and then the real time PCR (RT-PCR) machine was used for analysis. This study was particularly representing the impact of COVID-19 on suspected person. …”
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Association between plasma perfluoroalkyl substances and high-grade serous ovarian cancer overall survival: A nested case-control study by Wei-Yi Xing, Fang-Hua Liu, Dong-Dong Wang, Jia-Ming Liu, Wen-Rui Zheng, Jia-Xin Liu, Lang Wu, Yue-Yang Zhao, He-Li Xu, Yi-Zi Li, Yi-Fan Wei, Dong-Hui Huang, Xiao-Ying Li, Song Gao, Qi-Peng Ma, Ting-Ting Gong, Qi-Jun Wu

“…To elucidate the combined effects, Bayesian kernel machine (BKMR), and regression quantile g-computation (QGC) models were utilized. …”
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Algorithm for Cloud Particle Phase Identification Based on Bayesian Random Forest Method by Fu Tao, Yang Zhipeng, Tao Fa, Hu Shuzhen, Lu Yuxiang, Fu Changqing

“…Results in a high rate of misclassification when employing machine learning techniques for identifying the phase state of cloud particles.To accurately identify phases of cloud particles, a Bayesian Random Forest Method is employed, utilizing co-located millimeter-wave cloud radar and microwave radiometer observations. …”
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The association of origin and environmental conditions with performance in professional IRONMAN triathletes by Beat Knechtle, Mabliny Thuany, David Valero, Elias Villiger, Pantelis T. Nikolaidis, Marilia S. Andrade, Ivan Cuk, Thomas Rosemann, Katja Weiss

“…Data was analyzed using descriptive statistics and machine learning (ML) regression models. The models considered gender, country of origin, event location, water, and air temperature as independent variables to predict the final race time. …”
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Establishment and validation of predictive model of ARDS in critically ill patients by Senhao Wei, Hua Zhang, Hao Li, Chao Li, Ziyuan Shen, Yiyuan Yin, Zhukai Cong, Zhaojin Zeng, Qinggang Ge, Dongfeng Li, Xi Zhu

“…This study aimed to observe the incidence of ARDS among high-risk patients and develop and validate an ARDS prediction model using machine learning (ML) techniques based on clinical parameters. …”
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Relationship between stress hyperglycemia ratio and progression of non target coronary lesions: a retrospective cohort study by Shiqi Liu, Ziyang Wu, Gaoliang Yan, Yong Qiao, Yuhan Qin, Dong Wang, Chengchun Tang

“…Logistic regression models, restricted cubic spline analysis, and machine learning algorithms (LightGBM, decision tree, and XGBoost) were utilized to analyse the relationship of stress hyperglycemia ratio and non target lesion progression. …”
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Evaluation of Lacrimal Punctal Changes by Anterior Segment Optical Coherence Tomography after Punctal Dilation Versus Punctal Plug Insertion in Cases of Inflammatory Punctual Steno... by Islam Awny, Elshimaa A Mateen Mossa, Tasneem Mohammed Bakheet, Hany Mahmoud, Amr Mounir

“…OCT images of the width and length of the lower puncti of the participants were captured by the same operator on the same machine. Measuring of punctal size (diameter and length) was performed before treatment, one week, one month, and three months later objectively by using AS-OCT. …”
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Harmonizing population health data into OMOP common data model: a demonstration using COVID-19 sero-surveillance data from Nairobi Urban Health and Demographic Surveillance System by Michael Ochola, Sylvia Kiwuwa-Muyingo, Tathagata Bhattacharjee, David Amadi, Maureen Ng’etich, Damazo Kadengye, Henry Owoko, Boniface Igumba, Jay Greenfield, Jim Todd, Agnes Kiragga, Agnes Kiragga

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PlaceField2BVec: A bionic geospatial location encoding method for hierarchical temporal memory model by Zugang Chen, Shaohua Wang, Kai Wu, Guoqing Li, Jing Li, Jian Wang

“…Our research can be utilized for machine self-localization, navigation, and location-related GeoAI applications, and it also contributes to the theory of cognitive maps.…”
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Ekspresi Gen Family Bcl-2 dan Ekspresi Gen Protein Kanal Ion Vdac1 pada Oligozoospermia by Arni Amir

“…Gene Expression level was rated by using Light Cycler 2.0 machine (Roche).The Primer are designed using software primer 3 plus and primer specification that analyzed with Basic Local Alignment Search Tool (Blast). …”
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