Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

“…Performance was evaluated using accuracy, precision, recall, and F1-score metrics. …”
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Methylated SEPTIN9 plasma test for colorectal cancer detection may be applicable to Lynch syndrome by Maria Christensen, Andrew E Hendifar, Rachel Pearlman, Sigurdis Haraldsdottir, Albert de la Chapelle, Heather Hampel, Megan P Hitchins, Ingrid P Vogelaar, Kevin Brennan, Nianmin Zhou, Brock Martin, Rocio Alvarez, Xiaopu Yuan, Sungjin Kim, Maha Guindi, Matthew F Kalady, Jennifer DeVecchio, James M Church, Carrie Snyder, Stephen J Lanspa, Robert W Haile, Henry T Lynch

“…Secondly, to detect mSEPT9 as circulating tumor DNA, the plasma-based mSEPT9 test was retrospectively evaluated in LS subjects using the Epi proColon 2.0 CE assay adapted for 1mL plasma using the “1/1 algorithm”. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…Additionally, the immune and pathway scores of the training dataset samples were evaluated using the ESTIMATE, MCP-counter, and ssGSEA algorithms to establish the relationship between the hub genes and immune and pathways. …”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…Additionally, the study assessed the impact of various spectral indices on enhancing the results from the classification of Landsat 8 imagery, while also evaluating the efficacy of support vector machine (SVM) and maximum likelihood algorithms in producing maps with satisfactory accuracy and precision.   …”
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Identification of Disulfidptosis-Related Genes and Molecular Subgroups in Rheumatoid Arthritis for Diagnostic Model and Patient Stratification by Liu X, Wang S, Du X, Wang Y, Mo L, Li H, Qu Z, Wang X, Sun J, Li Y, Wang J

“…The machine learning algorithms were used to identify the hub genes. Second, a diagnostic model was constructed for RA based on the hub genes. …”
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Adaptation of the competence approach to the methodology of training it specialists in the field of programming by E. V. Savina, K. Ya. Radjabov, T. I. Isabekova

“…The research methods include: analysis of evaluation materials; methods based on algorithms for decomposing the program code proposed for solving the problem; methods for analyzing data from open sources, methods for analyzing algorithms and data structures. …”
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PRCFX-DT: a new graph-based approach for feature selection and classification of genomic sequences by Amin Khodaei, Sania Eskandari, Hadi Sharifi, Behzad Mozaffari-Tazehkand

“…The analysis of viral genomic sequences can be efficacious in evaluating the present and potentially forthcoming condition of viruses. …”
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Multi-omics analyses of the heterogenous immune microenvironment in triple-negative breast cancer implicate UQCRFS1 potentiates tumor progression by Yuhui Tang, Aiqi Xu, Zhongbiao Xu, Jindong Xie, Wei Huang, Liulu Zhang, Yitian Chen, Lu Yang, Shasha Du, Kun Wang

“…Methods The thorough analyses of different cell types within TME were conducted on the self-tested single-cell RNA sequencing dataset which contained nine TNBC treatment-naïve patients, including subclusters classification, CellChat algorithm, transcription factors (TFs) expression, pseudotime analysis and functional enrichment assay. …”
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Vascular anomalies in childhood. Review and update by Juan Carlos López Gutiérrez, Jesús Pozo Losada, Manuel Gómez Tellado

“…They are completely different diseases, although they are often grouped under the umbrella term of vascular anomalies.The diagnostic algorithm used in the clinical evaluation of vascular anomalies should be based on a thorough history-taking and detailed physical examination.Future knowledge in this field will be based above all on genetic findings and therapeutic innovations. …”
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Application of “high-fidelity and high-resolution” processing technology in thin reservoir identification: A case study of the deep Permian Maokou Formation in Penglai area, centra... by PENG Haotian, HE Qinglin, CHEN Kang, ZENG Ming, HE Zongqiang, TU Zhihui, KONG Lingxia, QU Bozhang

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Development and validation of MRI-based radiomics model for clinical symptom stratification of extrinsic adenomyosis by Man Sun, Jianzhang Wang, Ping Xu, Libo Zhu, Gen Zou, Shuyi Chen, Yuanmeng Liu, Xinmei Zhang

“…The relationship between magnetic resonance imaging (MRI) feature and symptom remains unclear.Objective To evaluate the performance of MRI radiomics model for differentiating symptom heterogeneity of extrinsic adenomyosis, pain, abnormal uterine bleeding (AUB), infertility, and no symptom.Materials and methods This retrospective analysis included 405 patients with MRI-diagnosed extrinsic adenomyosis (January 2020-July 2022), randomly split 7:3 into training and test cohorts. …”
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Machine Learning-Based VO₂ Estimation Using a Wearable Multiwavelength Photoplethysmography Device by Chin-To Hsiao, Carl Tong, Gerard L. Coté

“…Unlike conventional wearables that rely on static formulas for VO₂ max estimation, our algorithm leverages the data from the PPG wearable and uses the Beer–Lambert Law with inputs from five wavelengths (670 nm, 770 nm, 810 nm, 850 nm, and 950 nm), incorporating the isosbestic point at 810 nm to differentiate oxy- and deoxy-hemoglobin. …”
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INTERGENIC INTERACTIONS OF TUMOR NECROSIS FACTOR ALPHA, INTERLEUKIN 17, AND OSTEOPROTEGERIN IN THE IMMUNOPATHOGENESIS OF RHEUMATOID ARTHRITIS IN THE RUSSIAN POPULATION OF THE CHELY... by Yulia Chumacheva, Daria Stashkevich, Tatiana Suslova, Daria Shmelkova, Aleksandra Burmistrova

“…To analyse the data we applied the multifactor dimensionality reduction (MDR) algorithm, which constructs predictive case–control models and evaluates their robustness through ten-fold cross-validation and permutation testing.The algorithm identified three most informative combinations comprising four to six SNPs each; every combination showed statistical significance and high predictive accuracy. …”
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From genes to therapy: a lipid Metabolism-Related genetic risk model predicts HCC outcomes and enhances immunotherapy by Lei Xu, Ting Xiao, Tengfei Chao, Huihua Xiong, Wei Yao

“…The immune signature associated with the risk model was also evaluated by the CIBERSORT algorithm, tumor immune dysfunction and exclusion algorithm, and single sample gene set enrichment analysis. …”
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SegRep: Mask-Supervised Learning for Segment Representation in Pathology Images by Chichun Yang, Daisuke Komura, Mieko Ochi, Miwako Kakiuchi, Hiroto Katoh, Tetsuo Ushiku, Shumpei Ishikawa

“…However, this approach does not differentiate between tissue types, limiting component analysis. …”
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Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model‐based in silico evidence combined with g... by Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

“…Next, statistically, the postdoc test was used for the evaluation of treatments using SAS version 9.4, and p values of 0.05 and 0.01 were chosen for significant level. …”
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Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
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Assessing reading fluency in elementary grades: A machine learning approach by Gabriel Candido da Silva, Rodrigo Lins Rodrigues, Américo N. Amorim, Lieny Jeon, Emilia X.S. Albuquerque, Vanessa C. Silva, Vinícius F. da Silva, André L.A. Pinheiro, João P.J.R. Nunes, Suzana X.M.G. de Souza, Maxsuel S. Silva, Igor Mauro, Alexandre Magno Andrade Maciel

“…The research objective was to determine which algorithm best predicts fluency, considering diverse evaluation setups including binary classification (fluent versus non-fluent), multiclass classification (differentiated fluency levels), and regression analysis to estimate continuous fluency scores. …”
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Enhancing Lung Ultrasound Diagnostics: A Clinical Study on an Artificial Intelligence Tool for the Detection and Quantification of A-Lines and B-Lines by Mahdiar Nekoui, Seyed Ehsan Seyed Bolouri, Amir Forouzandeh, Masood Dehghan, Dornoosh Zonoobi, Jacob L. Jaremko, Brian Buchanan, Arun Nagdev, Jeevesh Kapur

“…<b>Methods</b>: The algorithm is evaluated on 692 lung ultrasound scans collected from 48 patients (65% males, aged: 55 ± 12.9) following their admission to an Intensive Care Unit (ICU) for COVID-19 symptoms, including respiratory failure, pneumonia, and other complications. …”
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Population-level predictive variation in machine learning diagnosis of symptomatic bacterial vaginosis by Diandra P. Ojo, Cameron Celeste, Dion Ming, Ruogu Fang, Ivana K. Parker

“…To determine the ability of ML models to perform equitably, this study evaluates the performance of ML algorithms in predicting symptomatic BV across different ethnic groups using 16S rRNA sequencing data. …”
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