Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…Furthermore, an optimal predictive model was developed for CKD using ten machine learning algorithms and enhanced model interpretability with the Shapley Additive Explanations (SHAP) method. …”
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Combining methylated RNF180 and SFRP2 plasma biomarkers for noninvasive diagnosis of gastric cancer by Zhihao Dai, Jin Jiang, Qianping Chen, Minghua Bai, Quanquan Sun, Yanru Feng, Dong Liu, Dong Wang, Tong Zhang, Liang Han, Litheng Ng, Jun Zheng, Hao Zou, Wei Mao, Ji Zhu

“…Materials & Methods: A total of 165 healthy individuals, 34 patients with precancerous gastric lesions, and 104 patients with confirmed GC were divided into training and validation sets; methylated RNF180 and SFRP2 were detected in circulating DNA from blood samples. Six models, including those based on logistic regression, Naive Bayes, K-nearest neighbor algorithm, glmnet, neural network, and random forest (RF) were built and validated. …”
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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…Underwater photogrammetry is challenged by image degradation caused by water absorption and scattering, which negatively impacts feature detection and 3D reconstruction quality. …”
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DIO-SLAM: A Dynamic RGB-D SLAM Method Combining Instance Segmentation and Optical Flow by Lang He, Shiyun Li, Junting Qiu, Chenhaomin Zhang

“…Feature points from moving objects can negatively impact the accuracy of Visual Simultaneous Localization and Mapping (VSLAM) algorithms, while detection or semantic segmentation-based VSLAM approaches often fail to accurately determine the true motion state of objects. …”
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Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation by Jingyi Hou, Jingyi Hou, Jingyi Hou, Lihan Wang, Lihan Wang, Naiqiang Zhu, Xueli Li

“…A protein-protein interaction (PPI) network of mitoDEGs was constructed, and hub mitoDEGs associated with MI were identified using CytoHubba and molecular complex detection (MCODE) algorithms. Transcription factor (TF) and microRNA (miRNA) targets of hub mitoDEGs were predicted using iRegulon and miRWalk plug-ins, respectively, and a regulatory network involving TFs, hub mitoDEGs, and miRNA was established. …”
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An innovative approach to urban parks and perception: a cross-cultural analysis using big and small data by Siqi Lai, Brian Deal

“…This study integrates big data (online reviews, images) and small data (survey results) with large language models (LLMs) and object detection algorithms to analyze public perceptions of urban parks in Stockholm, New York, and Shanghai. …”
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Effective deep learning aided vehicle classification approach using Seismic Data by Sherief Hashima, Mohamed H. Saad, Ahmad B. Ahmad, Takeshi Tsuji, Hamada Rizk

“…Traditional classification algorithms rely heavily on visual or sensor-based data (e.g., radar or image signals), often compromised by adverse weather, poor lighting, or occlusion. …”
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Analysis of the effectiveness of selection of women for coronarography in real clinical practice by N. V. Izmozherova, A. A. Popov, V. E. Sherstobitov

“…Severe coronary atherosclerosis was associated with absence of negative or doubtful results, whereas intact coronary vessels, negative and questionable results revealed more than half of the women. …”
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Utilizing bioinformatics to identify biomarkers and analyze their expression in relation to immune cell ratios in femoral head necrosis by Dongchen Li, Dongchen Li, Zhilong Huang, Teng Ma, Yu Su, Yu Su, Zhao Li, Zhao Li, Liang Sun, Ming Li, Zhong Li, Yao Li, Qian Wang, Yao Lu

“…BackgroundNecrosis of the Femoral Head (NFH) represents a challenging orthopedic condition, characterized by elusive early detection and rapid progression, predominantly in the middle-aged demographic. …”
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Hyperspectral Imaging and Machine Learning for Diagnosing Rice Bacterial Blight Symptoms Caused by <i>Xanthomonas oryzae</i> pv. <i>oryzae</i>, <i>Pantoea ananatis</i> and <i>Enter... by Meng Zhang, Shuqi Tang, Chenjie Lin, Zichao Lin, Liping Zhang, Wei Dong, Nan Zhong

“…This study explores the potential of combining hyperspectral imaging (HSI) with machine learning for the rapid and accurate detection of rice bacterial blight symptoms caused by various pathogens. …”
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Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Furthermore, temperature was identified as the most influential factor affecting residual crude oil content, exhibiting a significant negative correlation, while API gravity also showed a negative impact. …”
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Phasic and periodic change of drought under greenhouse effect by Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie, Peijun Rong

“…Purpose – Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. …”
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Social Media Suicide Watch by Katherine Prothro

“…Her own Twitter account revealed signals of her worsening mental health crisis.[1] While better content censoring could have helped, an algorithm capable of detecting her worsening mental state and alerting trusted individuals could have also served as a crucial safety net. …”
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Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

“…The random forest classifier, developed with HSFs, achieved the best performance in detecting the suicide risk among the models evaluated (accuracy=0.75, F1-score=0.70, recall=0.76, false negative rate=0.24). …”
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Exploring Machine Learning Methods for Aflatoxin M1 Prediction in Jordanian Breast Milk Samples by Abdullah Aref, Eman Omar, Eman Alseidi, Nour Elhuda A. Alqudah, Sharaf Omar

“…The presence of aflatoxin M1 in breast milk poses a serious risk to the health of infants because of its potential to cause cancer and have negative effects on development. Detecting AFM1 in milk samples using conventional methods is often time-consuming and may not provide real-time monitoring capabilities. …”
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Tactical features of the scene inspection in the investigation of the taking of a government official or law enforcement officer as a hostage by O. Yu. Prokopenko

“…However, in the course of the study of scientific findings, the absence of methodological recommendations for investigating this crime has been established, which negatively affects the state of combating crime. In particular, the investigation methodology includes recommendations on the specifics of certain investigative (detective) actions, the primary of which is the inspection of the scene. …”
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Clusters from chronic conditions in the Danish adult population. by Anders Stockmarr, Anne Frølich

“…We find that subdivision into municipality levels suggests that the Allergies cluster frequency is positively associated with socioeconomic status, while the subdivision suggests that frequencies for clusters Diabetes and Hypercholesterolemia are negatively correlated with socioeconomic status. We detect no indication of association to socioeconomic status for the Chronic Heart Conditions cluster and the Musculoskeletal and Psychiatric Conditions cluster. …”
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Preeclampsia pathogenesis and prediction - where are we now: the focus on the role of galectins and miRNAs by Natasa Karadzov Orlic, Ivana Joksić

“…Preeclampsia is a complex, progressive multisystem hypertensive disorder during pregnancy that significantly contributes to increased maternal and perinatal morbidity and mortality. Two screening algorithms are in clinical use for detecting preeclampsia: first-trimester screening, which has been developed and validated for predicting early-onset preeclampsia but is less effective for late-onset disease; and the sFlt-1:PlGF biomarker ratio (soluble tyrosine kinase and placental growth factor) used in suspected cases of preeclampsia. …”
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A Portable UV-LED/RGB Sensor for Real-Time Bacteriological Water Quality Monitoring Using ML-Based MPN Estimation by Andrés Saavedra-Ruiz, Pedro J. Resto-Irizarry

“…Fluorescence signals from individual wells are captured by the RGB sensors and analyzed using Multilayer Perceptron Neural Network (MLPNN) and Support Vector Machine (SVM) algorithms, which can quickly determine if individual wells will be positive or negative by the end of a 24 h period. …”
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Constitutional-Legal Aspect of Creating Large Language Models: the Problem of Digital Inequality and Linguistic Discrimination by I. G. Ilin

“…While direct forms of discrimination can be detected in predictive algorithms, generative models create more subtle but no less significant cumulative effects. …”
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