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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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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GALNT6 associated with O-GlcNAcylation contributes to the tumorigenesis of oral squamous cell carcinoma by Junfeng Yan, Xuan Tang, Yingying Zhou, Xin Xiong

“…O-GlcNAcylation related genes with differential expression were screened and filtered by LASSO, RF and SVM machine learning models. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…NDVI data were screened for outliers using the interquartile range method. …”
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The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature by Zohreh Fazli, Mehran Sadeghi, Mohebat Vali, Parvin Ahmadinejad

“…After removing duplicate references, screened based on title, keywords, and abstract, Ultimately, 59 eligible articles were selected, which utilized various artificial intelligence tools, such as expert systems, machine learning, deep learning, and other applied AI models. …”
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Comprehensive bioinformatics analysis of the common mechanism of atherosclerosis and atrial fibrillation: emphasizing mitochondrial metabolic disorder and immune inflammation by Rui Dai, Xiaotong Lei, Xiaojun Liu, Chen Bian

“…Three machine learning algorithms (LASSO, SVM, and random forest) were applied to screen hub genes, followed by validation in independent datasets. …”
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Exposure patterns and the risk factors of Crimean Congo hemorrhagic fever virus amongst humans, livestock and selected wild animals at the human/livestock/wildlife interface in Isi... by Eugine Mukhaye, James M Akoko, Richard Nyamota, Athman Mwatondo, Mathew Muturi, Daniel Nthiwa, Lynn J Kirwa, Joel L Bargul, Hussein M Abkallo, Bernard Bett

“…Serum samples from all recruited humans and animals were collected and screened for CCHFV antibodies using ID Screen multispecies, double-antigen IgG enzyme-linked immunosorbent assay (ELISA). …”
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Software and Hardware Control System for Implementing the Balance Error Scoring System by Oksana Blavt, Gennadii Iedynak, Lesia Galamanzhuk, Tetyana Helzhynska, Yurii Kachurak, Yulia Mykhalskа, Liubov Levandovska, Rostyslav Tymkovych

“…For real-time data transmission to the PC screen and smartphone, wireless modules HC-05 (Bluetooth) or ESP32 (Wi-Fi) were used. …”
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Sodium Propionate Alleviates Atopic Dermatitis by Inhibiting Ferroptosis via Activation of LTBP2/FABP4 Signaling Pathway by Xie A, Li W, Ye D, Yin Y, Wang R, Wang M, Yu R

“…Analysis using three algorithms identified potential therapeutic targets of SP. …”
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Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Subsequent analyses included functional enrichment, gene interaction, and protein-protein interaction (PPI) network construction. Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. …”
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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Identification of subtypes and biomarkers associated with disulfidptosis-related ferroptosis in ulcerative colitis by Yinghao Jiang, Hongyan Meng, Xin Zhang, Jinguang Yang, Chengxin Sun, Xiaoyan Wang

“…Next, the hub genes were identified by differential analysis and WGCNA algorithms, and three machine learning algorithms were used to screen biomarkers for UC from hub genes. …”
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Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases ac... by Fuxu Wang, Yu Guo, Yuru Tang, Shuangmei Zhao, Kaige Xuan, Zhi Mao, Ruogu Lu, Rongyao Hou, Xiaoyan Zhu

“…Five ML algorithms were employed for mortality risk prediction, with SHapley Additive exPlanations (SHAP) applied to identify critical predictors. …”
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