A comprehensive analysis identified an autophagy-related risk model for predicting recurrence and immunotherapy response in stage I lung adenocarcinoma by Hongmei Zheng, Songqing Fan, Hongjing Zang, Jiadi Luo, Long Shu, Jinwu Peng

“…Gene set enrichment analysis (GSEA) was used to reveal the molecular features of patients. ESTIMATE algorithm was applied to estimate the tumor immune infiltration. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…For its part, PSO optimizes design and manufacturing parameters for the materials, raising their efficiency by 10–15%, while the energy consumption goes down by 8–12%. …”
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Unraveling the role of gut microbiome in predicting adverse events in neoadjuvant therapy for rectal cancer by Jingxin Ma, Shengbo Sun, Xin Cheng, Cong Meng, Hanzheng Zhao, Wentao Fu, Yan Gao, Liyan Ma, Zhengyang Yang, Hongwei Yao, Jianrong Su

“…Boc-beta-cyano-L-alanine and CoQ9 were significantly increased in patients without adverse events, while linoleic acid increased in patients with adverse events. …”
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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome by Pedro Pons-Suñer, François Signol, Noemi Alvarez, Claudia Sargas, Sara Dorado, Jose Vicente Gil Ortí, Juan A. Delgado Sanchis, Marta Llop, Laura Arnal, Rafael Llobet, Juan-Carlos Perez-Cortes, Rosa Ayala, Eva Barragán

“…First, to evaluate a feature selection methodology based on SEQENS, an algorithm for identifying relevant variables. Second, to validate machine learning models that predict the risk of complications in patients with acute myeloid leukemia (AML) using data available at diagnosis. …”
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Deconvolution of cell types and states in spatial multiomics utilizing TACIT by Khoa L. A. Huynh, Katarzyna M. Tyc, Bruno F. Matuck, Quinn T. Easter, Aditya Pratapa, Nikhil V. Kumar, Paola Pérez, Rachel J. Kulchar, Thomas J. F. Pranzatelli, Deiziane de Souza, Theresa M. Weaver, Xufeng Qu, Luiz Alberto Valente Soares Junior, Marisa Dolhnokoff, David E. Kleiner, Stephen M. Hewitt, Luiz Fernando Ferraz da Silva, Vanderson Geraldo Rocha, Blake M. Warner, Kevin M. Byrd, Jinze Liu

“…To address this, we develop TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. …”
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Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

“…Additionally, the label noise estimation algorithm (confident learning) cannot fully identify label noise. …”
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Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis by Myles J. Lewis, Cankut Çubuk, Anna E. A. Surace, Elisabetta Sciacca, Rachel Lau, Katriona Goldmann, Giovanni Giorli, Liliane Fossati-Jimack, Alessandra Nerviani, Felice Rivellese, Costantino Pitzalis, the STRAP collaborative group

“…Abstract Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…The viewing geometry had limited effects on the choice of preprocessing method and retrieval algorithm. Among the preprocessing methods, D1, SG + D1, and SG + D2 outperformed the others, while PLSR achieved a higher accuracy than SVM and CNN when retrieving soil properties. …”
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Comparison of UAV-Based LiDAR and Photogrammetric Point Cloud for Individual Tree Species Classification of Urban Areas by Qixia Man, Xinming Yang, Haijian Liu, Baolei Zhang, Pinliang Dong, Jingru Wu, Chunhui Liu, Changyin Han, Cong Zhou, Zhuang Tan, Qian Yu

“…The results indicate that LiDAR outperformed DAP in individual tree segmentation (F-score 0.83 vs. 0.79), while DAP achieved higher pixel-level classification accuracy (73.83% vs. 57.32%) due to spectral-textural features. …”
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Investigating Whether AI Will Replace Human Physicians and Understanding the Interplay of the Source of Consultation, Health-Related Stigma, and Explanations of Diagnoses on Patien... by Weiqi Guo, Yang Chen

“…This provides insights for the design of AI medical agents, which have long been criticized for lacking transparency while making highly consequential decisions. This study concludes by outlining theoretical contributions to research on health communication and human-AI interaction and discusses the implications for the design and application of medical AI.…”
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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The VIF values ranged between 1.12 and 8.73, with VH_Jan_Mar having the maximum VIF and forest canopy height having the minimum VIF. As per the Boruta algorithm, 16 attributes were deemed important, while 14 attributes had less influence on AGB. …”
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Augmenting Naïve Bayes Classifiers with <i>k</i>-Tree Topology by Fereshteh R. Dastjerdi, Liming Cai

“…Therefore, this algorithm can be employed to ensure efficient approximation of Bayesian networks with <i>k</i>-tree augmented Naïve Bayesian classifiers of the guaranteed minimum loss of information.…”
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Fertility, Hatchability, and Prediction of Egg Weight from Egg Quality Indices of Nigerian Indigenous and Exotic Helmeted Guinea Fowls by Praise Jegede, Abdulmojeed Yakubu, Ibrahim S. Musa, Samuel T. Vincent, Ayoola J. Shoyombo, Olayinka O. Alabi, Mathew Wheto, Ayotunde O. Adebambo, Mustapha A. Popoola

“…Three principal components sufficiently accounted for the variations in the egg quality traits of both genetic groups. The CHAID algorithm was more consistent in egg weight prediction, with egg width as the primary explanatory variable. …”
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A Novel Approach to Generate a Virtual Population of Human Coronary Arteries for <italic>In Silico</italic> Clinical Trials of Stent Design by Dimitrios Pleouras, Antonis Sakellarios, George Rigas, Georgia S. Karanasiou, Panagiota Tsompou, Gianna Karanasiou, Vassiliki Kigka, Savvas Kyriakidis, Vasileios Pezoulas, George Gois, Nikolaos Tachos, Aidonis Ramos, Gualtiero Pelosi, Silvia Rocchiccioli, Lampros Michalis, Dimitrios I. Fotiadis

“…<italic>Methods:</italic> A clinical data augmentation algorithm is implemented to efficiently generate virtual clinical data using a real clinical dataset. …”
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Post–below-knee amputation venous thromboembolism and mortality in United States veterans by Khanh P. Nguyen, Joshua B. Gruber, Megan L. Mertzel, Cecelia Madison, Reid Thompson, Kenneth Gundle, Scott Damrauer, Kristen M. Sanfilippo

“…We identified VTE within 90 days post-BKA using a previously validated algorithm combining International Classification of Diseases codes with a new anticoagulant prescription, placement of an inferior vena cava filter, or death within 30 days. …”
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Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes by Mohammad Rashidmayvan, Amin Mansoori, Elahe Derakhshan-Nezhad, Davoud Tanbakuchi, Fatemeh Sangin, Maryam Mohammadi-Bajgiran, Malihehsadat Abedsaeidi, Sara Ghazizadeh, MohammadReza Mohammad Taghizadeh Sarabi, Ali Rezaee, Gordon Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…We aimed to investigate the relationship between intake of macro/micronutrients and the incidence of type 2 diabetes (T2D) using logistic regression (LR) and a decision tree (DT) algorithm for machine learning. Method Our research explores supervised machine learning models to identify T2D patients using the Mashhad Cohort Study dataset. …”
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Subtypes of tic disorders in children and adolescents: based on clinical characteristics by Kai Yang, Wenyan Zhang, Ying Li, Xianbin Wang, Zhongliang Jiang, Shujin Hu, JinHyun Jun, Qinghao Yang, Jingyi Li, Xu Hong, Yonghua Cui, Tianyuan Lei

“…The k-means clustering algorithm was used to identify distinct TD subtypes. …”
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Identification and Characterization of Genes Associated with Intestinal Ischemia-Reperfusion Injury and Oxidative Stress: A Bioinformatics and Experimental Approach Integrating Hig... by Xie Y, Yang M, Huang J, Jiang Z

“…The least absolute shrinkage and selection operator, as well as the support vector machine with random forest algorithm, were utilized for machine learning. Subsequently, the PPI network was established, and the Degree and MNC algorithms of the Cytohuba plugin were integrated with the genes obtained through the machine learning algorithms to identify hub IOSRGs (HIOSRGs). …”
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Invisible Manipulation: Deep Reinforcement Learning-Enhanced Stealthy Attacks on Battery Energy Management Systems by Qi Xiao, Lidong Song, Jong Ha Woo, Rongxing Hu, Bei Xu, Kai Ye, Ning Lu

“…Testing on the same testbed allows real-time evaluation of microgrid responses, where the BEMS, EKF-based SoC estimation algorithms interact dynamically with the injected false measurements. …”
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Integrative analysis of epigenetic subtypes in acute myeloid Leukemia: A multi-center study combining machine learning for prognostic and therapeutic insights. by Jincan Li, Shengyue Wang

“…High-risk patients exhibited distinct immune profiles with elevated M2 macrophages (1.8-fold) and Tregs (2.3-fold), while low-risk patients showed enhanced NK cell activity (2.1-fold). …”
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