Classification of left and right-hand motor imagery in acute stroke patients using EEG microstate by Shiyang Lv, Xiangying Ran, Mengsheng Xia, Yehong Zhang, Ting Pang, Xuezhi Zhou, Zongya Zhao, Yi Yu, Zhixian Gao

“…Significant features were used to construct classification models using Linear Discriminant Analysis(LDA), Support Vector Machines(SVM), and K-Nearest Neighbors(KNN) algorithms. …”
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Uncovering Hippo pathway-related biomarkers in acute myocardial infarction via scRNA-seq binding transcriptomics by Xingda Li, Xueqi He, Yu Zhang, Xinyuan Hao, Anqi Xiong, Jiayu Huang, Biying Jiang, Zaiyu Tong, Haiyan Huang, Lian Yi, Wenjia Chen

“…Candidate genes were derived from intersecting initial DEGs with subtype-associated DEGs. Three machine-learning algorithms prioritized five biomarkers (NAMPT, CXCL1, CREM, GIMAP6, and GIMAP7), validated through multi-dataset analyses and cellular expression profiling. qRT-PCR and Western blot confirmed differential expression patterns between AMI and controls across experimental models. …”
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Unraveling anoikis in glioblastoma: insights from single-cell sequencing and prognostic modeling by Qikai Tang, Chenfeng Ma, Jiaheng Xie, Qixiang Zhang, Bingtao Zhang, Weiqi Bian, Qingyu Lu, Zeyu Wan, Wei Wu

“…We identified anoikis-related genes, constructed a prognostic model using 101 machine learning algorithms, and validated its clinical utility across multiple cohorts.Finally, we also verified the expression of model genes and the function of key gene in clinical samples and cell lines. …”
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Exploring the Current Applications and Future Implications of Artificial Intelligence in Public Health Dentistry: A Narrative Review by Tanushri Mahendra Dalvi, Rajeshri Kotwadekar, Shrivardhan R Kalghatgi, Priyanka Paul Madhu, Priyanka Methildeotare

“…AI applications can also be utilised in epidemiologic surveillance for analysis of health-related information in forecasting disease patterns and drafting evidence based public health policies. …”
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Digital remote monitoring of people with multiple sclerosis by Michelangelo Dini, Michelangelo Dini, Giancarlo Comi, Letizia Leocani, Letizia Leocani, Letizia Leocani

“…We focus on tools and techniques applied to data from wearable sensors, smartphones, and other connected devices, as well as AI-based methods for the analysis of big data.ResultsWearable sensors and machine learning algorithms show significant promise in monitoring motor symptoms, such as fall risk and gait disturbances. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Network Intrusion Detection Systems (NIDS) are critical in ensuring the security of connected computer systems by actively detecting and preventing unauthorized activities and malicious attacks. Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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Identification of key genes and immune infiltration mechanisms in limb ischemia-reperfusion injury: a bioinformatics and experimental study by Qiyun Shi, Taotao Tian, Yanfeng Li

“…Immune cell infiltration patterns were analyzed via CIBERSORT.ResultsFrom 169 differentially expressed genes (116 upregulated, 53 downregulated), machine learning identified four key genes (WNT5A, PLCG, ITPR1, CAMK2A), significantly upregulated in experimental limb IRI (P<0.01). …”
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Thymic characteristics in patients with autoimmune diseases: a multicentre radiological observational studyResearch in context by Haoxiao Chang, Junqiang Yan, Anxin Wang, Ningning Wang, Peng Liu, Yemin Shi, Xin Zhao, Jinqiao Zhu, Yuan Cai, Xue Xia, Yunyi Hao, Shiyi Yin, Jing Wang, Xinli Wang, Lina Sun, Jia Ma, Xiaoyu Huang, Haonan Guan, De-Cai Tian, Kaibin Shi, Ganqin Du, Wenhao Huang, Guoyan Qi, Hao Li, Yongjun Wang, Fu-Dong Shi, Zhang Zhang, Wei-Na Jin

“…Interpretation: Radiological assessments reveal a consistent pattern of exacerbated age-dependent thymic involution across 16 autoimmune diseases, suggesting a common underlying mechanism in the development of these diseases. …”
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Artificial Intelligence and Ethical Dimensions of Automated Traffic Enforcement: Implications for Public Health, Healthcare Equity, and Social Justice by Patricia Haley

“…The analysis reveals how machine learning and predictive analytics in automated enforcement create disproportionate burdens on marginalized populations through three specific mechanisms: (1) biased algorithmic design that targets low-income neighborhoods more intensively, (2) punitive traffic fine structures that impose greater relative financial hardship on economically disadvantaged families, and (3) opaque implementation practices that limit community understanding and participation. …”
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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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Oligogenic analysis across broad phenotypes of 46,XY differences in sex development associated with NR5A1/SF-1 variants: findings from the international SF1next studyResearch in co... by Chrysanthi Kouri, Idoia Martinez de Lapiscina, Rawda Naamneh-Elzenaty, Grit Sommer, Kay-Sara Sauter, Christa E. Flück, Saygin Abali, Zehra Yavas Abali, S. Faisal Ahmed, Leyla Akin, Maricruz Almaraz, Laura Audí, Murat Aydin, Antonio Balsamo, Federico Baronio, Jillian Bryce, Kanetee Busiah, Maria Caimari, Núria Camats-Tarruella, Ariadna Campos-Martorell, Luis Castaño, Anna Casteràs, Semra Çetinkaya, Hedi L. Claahsen - van der Grinten, Martine Cools, Ines Costa, Fatma Feyza Darendeliler, Justin H. Davies, Isabel Esteva, Helena Fabbri-Scallet, Courtney A. Finlayson, Emilio Garcia, Beatriz Garcia- Cuartero, Alina German, Evgenia Globa, Gil Guerra-Junior, Julio Guerrero, Tulay Guran, Sabine E. Hannema, Olaf Hiort, Josephine Hirsch, Ieuan Hughes, Marco Janner, Uchenna Kennedy, Zofia Kolesinska, Katherine Lachlan, Anna Lauber-Biason, Jana Krenek Malikova, Dagmar L’Allemand, Nina Lenhnerr-Taube, Angela Lucas-Herald, Jamala Mammadova, Veronica Mericq, Isabel Mönig, Francisca Moreno, Julia Mührer, Marek Niedziela, Anna Nordenstrom, Burçe Orman, Sukran Poyrazoglu, Jose M. Rial, Meilan M. Rutter, Amaia Rodríguez, Tara Schafer-Kalkhoff, Sumudu Nimali Seneviratne, Maria Sredkova-Ruskova, LIoyd J.W. Tack, Rieko Tadokoro-Cuccaro, Ajay Thankamony, Mónica Tomé, Amaia Vela, Malgorzata Wasniewska, David Zangen, Nataliya Zelinska

“…Interpretation: These findings highlight the complex genetic landscape of DSD associated with NR5A1/SF-1, where in several cases, the use of advanced genetic testing and filtering with specific algorithms and machine learning tools revealed additional genetic hits that may contribute to the phenotype. …”
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Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms by Jing Mao, Jianping Lan, Zheyu Zhuang, Ying Chen, Ying Chen, Yushan Ou, Xinhong Su, Xueting Zeng, Fuchen Huang, Zequn Tong, Xiaoqing Lv, Xiaoqing Lv, Xiaoqing Lv, Hui Ke, Zhenlan Wu, Ying Zou, Bo Cheng, Bo Cheng, Bo Cheng, Chao Ji, Chao Ji, Chao Ji, Ting Gong

“…Weighted Gene Co-expression Network Analysis (WGCNA) was employed to identify co-expressed gene modules related to pemphigus. Machine learning algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to select key ferroptosis-related genes. …”
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Spatio-temporal distribution, prediction and relationship of three major acute cardiovascular events: Out-of-hospital cardiac arrest, ST-elevation myocardial infarction and stroke by Angelo Auricchio, Tommaso Scquizzato, Federico Ravenda, Ruggero Cresta, Stefano Peluso, Maria Luce Caputo, Stefano Tonazzi, Claudio Benvenuti, Antonietta Mira

“…All the three diseases showed a similar spatial pattern. Conclusions: Prediction of incidence of OHCA, STEMI, and stroke is possible with very high accuracy using INLA and MLMM models. …”
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Simulating the root-to-shoot ratio of natural grassland biomass in China by the AutoGluon framework by Rui Guo, Xiaodong Huang, Yangjing Xiu, Minglu Che, Jinlong Gao, Shuai Fu, Qisheng Feng, Tiangang Liang

“…In this study, a high-accuracy R/S model was constructed using the AutoGluon framework and traditional machine learning (ML) algorithms with 1,367 R/S samples of grassland in China, integrating climate, soil, terrain and spectral features. …”
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A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization by Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu

“…Predicting recurrence after lumbar disc herniation (LDH) remains clinically important but algorithmically difficult due to extreme class imbalance and low signal-to-noise ratio. …”
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Novel multi-omics analysis revealing metabolic heterogeneity of breast cancer cell and subsequent development of associated prognostic signature by Peng Zhang, Cuicui Li, Fen Li, Jiezhong Wu, Kunpeng Hu, He Huang

“…A metabolic risk signature was constructed using machine learning algorithms. Immune cell infiltration and immune checkpoint profiles were assessed to explore tumor microenvironment differences. …”
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Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications by You Wu, Kunyu Wang, Yan Song, Bin Li

“…The AIDPI model was developed and refined using univariate Cox regression analysis and an ensemble of machine learning algorithms. Functional analysis, immunoprofiling, and the role of the MFAP4 gene were investigated to elucidate the biological mechanisms underlying the model. …”
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Identification and validation of biomarkers, construction of diagnostic models, and investigation of immunological infiltration characteristics for idiopathic frozen shoulder by Han-tao Jiang, Li-ping Shen, Meng-Qi Pang, Min-jiao Wu, Jiang Li, Wei-jie Gong, Gang Jin, Rang-teng Zhu

“…At the outset, we conducted differential expression analysis, weighted gene co-expression network analysis (WGCNA), and utilized the cytoHubba plugin, complemented by two machine learning algorithms, receiver operating characteristic (ROC) analysis, and expression level evaluation to identify biomarkers for FS. …”
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Deciphering Socio-Spatial Integration Governance of Community Regeneration: A Multi-Dimensional Evaluation Using GBDT and MGWR to Address Non-Linear Dynamics and Spatial Heterogene... by Hong Ni, Jiana Liu, Haoran Li, Jinliu Chen, Pengcheng Li, Nan Li

“…Our findings reveal critical intersections where residential density thresholds interact with commercial accessibility patterns and transport network configurations. Notably, we highlight the scale-dependent influence of educational proximity and healthcare distribution on community satisfaction, challenging conventional planning doctrines that rely on static buffer-zone models. …”
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AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…By analyzing vast datasets, AI can uncover hidden fraud patterns and dynamically adapt to emerging threats. …”
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