Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In order to solve these problems, this study constructs a benchmark dataset of the feeding intensity of pearl gentian groupers in a factory circulating water environment, which is divided into feeding fish groups and fish aggregation areas by training Unet semantic segmentation network and compares standard clustering algorithms through clustering evaluation indexes to maximally select the optimal clustering method and the number of clusters that are suitable for this paper's dataset. …”
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A Spatiotemporal Fusion Network for Remote Sensing Based on Global Context Attention Mechanism by Weisheng Li, Yusha Liu, Yidong Peng, Fengyan Wu

“…Spatial-temporal fusion algorithms commonly encounter difficulties in effectively striking a balance between the extraction of intricate spatial details and changes over time. …”
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The Current Role and Prospects of Electrophysiological Research Methods in Ophthalmology. Literature Review by V. N. Kazajkin, V. O. Ponomarev, A. V. Lizunov, A. E. Zhdanov, A. Yu. Dolganov, V. I. Borisov

“…This leaves the possibility and the need for the study, optimization and algorithmization of the assessment data of the differentiated criteria inherent for a particular ocular pathology. …”
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Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo. by Audêncio Victor, Diego Augusto Medeiros Santos, Eduardo Koerich Nery, Danilo Pereira Mori, Pamella Cristina de Carvalho Lucas, Denise Cammarota, Guillermo Leonardo Florez Montero, Fabiano Novaes Barcellos Filho, Ana Lúcia Frugis Yu, Telma Regina Marques Pinto Carvalhanas

“…<h4>Conclusion</h4>ML algorithms, particularly CatBoost, XGBoost, and LightGBM, proved highly effective in the differential diagnosis of meningitis, offering a valuable tool for the rapid identification of meningitis types and bacterial serogroups. …”
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Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…In studies evaluating onychomycosis, AI has shown the ability to distinguish between normal nails, fungal infections, and other differentials, including nail psoriasis, with a high accuracy. …”
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Global progress in competitive co-evolution: a systematic comparison of alternative methods by Stefano Nolfi, Paolo Pagliuca

“…The selected algorithms promote genuine progress by creating an archive of opponents used to evaluate evolving individuals, generating archives that include high-performing and well-differentiated opponents, identifying and discarding variations that lead to local progress only (i.e., progress against the opponents experienced and retrogressing against others). …”
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Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma by Gang Wang, Jiaxing Zhang, Yirong Li, Yuyu Zhang, Weiwei Dong, Hengquan Wu, Jinglan Wang, Peiqing Liao, Ziqiang Yuan, Tao Liu, Wenting He

“…Three machine-learning algorithms were used to identify shared diagnostic genes. …”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

“…This study integrates the population–development–environment model with back propagation (BP) neural networks, a supervised learning algorithm, to analyze how differentiated development trajectories reshape land systems. …”
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Comprehensive analysis of single-cell and bulk RNA sequencing data unveils antigen-presenting and processing fibroblasts and establishes a predictive model in gastric cancer by Chenggang Zhang, Fangqi Chen, Jie Li, Yixuan He, Juan Sun, Zicheng Zheng, Guanmo Liu, Yihua Wang, Weiming Kang, Xin Ye

“…CellChat algorithm was utilized to evaluate interactions between cells. …”
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Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy by Wei Wu, Qihan Fu, Lulu Liu, Yi Zheng, Hangyu Zhang, Peng Zhao, Weijia Fang, Xuanwen Bao, Shaobing Cheng, Xiaomeng Dai, Xudong Zhu, Zhou Tong, Fanglong Liu

“…The association of the mutation pattern and microsatellite status was analyzed by a random forest algorithm in The Cancer Genome Atlas (TCGA) and validated by our in-house dataset (39 tumor mutational burden (TMB)-low MSS colon cancer, 10 TMB-high MSS colon cancer, 15 MSI colon cancer). …”
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3D conformation and crystal interaction insights into drug development challenges for HCV drug analogues via molecular simulations by Richard S. Hong, Alessandra Mattei, Mark E. Tuckerman, Ahmad Y. Sheikh

“…In this article, we demonstrate how a suite of molecular simulation approaches, including crystal structure prediction augmented with a new hydrate CSP algorithm, free-energy perturbation, molecular dynamics (MD) based solubility predictions, and topological assessment to evaluate surface re-crystallization tendencies, provide key atomistic-level insights into the differentiated performance of the two analogs. …”
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Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy by Tao Zhou, Hua Cai, Lisha Wu, Jianjun Chen, Liuqing Zhou, Jun Liu

“…A PPI network of differentially expressed autophagy-related genes were established and further identified through the CytoHubba algorithm. …”
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Risk prediction and analysis of gallbladder polyps with deep neural network by Kerong Yuan, Xiaofeng Zhang, Qian Yang, Xuesong Deng, Zhe Deng, Xiangyun Liao, Weixin Si

“…To address the need for accurate prediction, we introduced a novel neural network learning algorithm. This algorithm utilizes the aforementioned risk factors to predict the nature of gallbladder polyps. …”
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Shared pathogenic mechanisms linking obesity and idiopathic pulmonary fibrosis revealed by bioinformatics and in vivo validation by Linjie Chen, Haojie Chen, Zinan Chen, Kunyi Zhang, Hongsen Zhang, Jiahe Xu, Tongsheng Chen

“…Functional enrichment (GO/KEGG), protein-protein interaction (PPI) networks, and machine learning algorithms were applied to screen hub genes, validated by ROC curves. …”
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Identification of marker genes associated with oxidative stress in hypertrophic cardiomyopathy using bioinformatics analysis and experimental validation by Jian Zhuo, Ding Ding, Mengkang Fan, Weiwei Lu, Xiaochen Lu, Lihong Yao, Hongzhuan Sheng

“…GSE36961 and GSE141910 were downloaded from the Gene expression Omnibus (GEO) database, and genes associated with oxidative stress were searched in the Gene Ontology (GO) database. After differential analysis, marker genes were obtained using LASSO and SVM-RFE algorithms. …”
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Molecular insights into ulcerative colitis and orbital inflammation by Kang Tan, Pei Liu, Zixuan Wu, Xi Long, Yunfeng Yu, Pengfei Jiang, Qinghua Peng

“…Machine learning algorithms identified eight potential genes for diagnostic and therapeutic use, with CXCL10 emerging as a key player in the pathogenesis of NSOI and UC. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…Univariate analysis was used to examine differential indicators, and variable selection was conducted through LASSO regression. …”
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S100A7 as a predictive biomarker in malignant transformation of oral epithelial dysplastic lesions by Jeffrey Soparlo, Lachlan McLean, Christina McCord, Linda Jackson-Boeters, Michael Shimizu, Michael Robinson, Wanninayake M. Tilakaratne, Mark R. Darling

“…The objective of this study was to evaluate S100A7 expression in OPMD which transformed and to correlate these results with the 3-tier and 2-tier dysplasia grading systems, and an S100A7 immunohistochemistry-based signature algorithm (S100A7 ARS). …”
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Integrative bioinformatics analysis identifies METTL1 as a regulator of immune infiltration and prognosis in breast cancer by Xiao-bin Lin, Yu-zhi Yao, Hong-min Ma, Cai-rong Zhu, Qi-rong Wen

“…Co-expressed genes and differentially expressed genes related to METTL1 were identified using Pearson correlation and Wilcoxon tests, with overlapping genes subjected to protein-protein interaction network construction to identify hub genes via degree algorithm. …”
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An Explainable CatBoost Model for Crater Classification Based on Digital Elevation Model by Minghao Zhu, Jialong Lai, Xiaoping Zhang, Yi Xu, Weidong He

“…In this study, we propose a machine-learning-based approach using the CatBoost algorithm to classify craters based on variables extracted from Digital Elevation Model (DEM) data. …”
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