ZBTB10 as a potential prognosis biomarker and correlates with the tumor immune microenvironment in stomach adenocarcinoma by Yingdi Jiang, Fuhua Han, Lu Dai, Shali Qiu, Yanjie Zhou, Ke Wang, Jiang Lin

“…UALCAN and TCGA databases were used to evaluate the association of ZBTB10 expression with clinicopathological characteristics. …”
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The value of a radiomics model in predicting ovarian malignancy: a retrospective multi-center comparison with O-RADS and radiologists by Junjie Jin, Xijia Deng, Ling Long, Meiling Liu, Meimei Cao, Hao Gong, Huan Liu, Xiaosong Lan, Lili Liu, Jiuquan Zhang

“…Features were selected using minimum redundancy, maximum relevance, and the least absolute shrinkage and selection operator algorithm. Diagnostic performance of the radiomics model, O-RADS, and independent assessments by junior and senior radiologists was evaluated via the area under the receiver operating characteristic curve (AUC) and compared using DeLong’s test. …”
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Immune regulatory genes impact the hot/cold tumor microenvironment, affecting cancer treatment and patient outcomes by Mengmeng Sang, Jia Ge, Juan Ge, Juan Ge, Gu Tang, Qiwen Wang, Jiarun Wu, Liming Mao, Liming Mao, Xiaoling Ding, Xiaorong Zhou

“…Kyoto Encyclopedia of Genes and Genomes and Hallmark pathway enrichment were evaluated through gene set variation analysis. Additionally, hub genes that regulate the tumor microenvironment were identified, and their expression patterns were analyzed using single-cell RNA sequencing. …”
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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

“…The nomogram using the LightGBM algorithm reached the best AUC (0.966, 95% CI: 0.927–1.000). …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. …”
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Comparative estimation of the effectiveness of the Khorana, Vienna CATS, and TiC-Onco scores and the vWF/ADAMTS13 ratio in identifying a high risk of thrombotic complications in pa... by A. V. Vorobеv, A. G. Solopova, V. O. Bitsadze, M. M. Baeva, M. E. Sosnyagova, V. N. Galkin, D. O. Utkin, A. D. Makatsariya

“…Objective: To compare the diagnostic accuracy of the Khorana, Vienna CATS, and TiC-Onco scores in assessing the risk of venous thromboembolism (VTE) in patients with malignant neoplasms of the female reproductive system and mammary gland and to evaluate the prognostic role of the vWF/ADAMTS13 ratio in identifying groups with a high risk of thrombosis.Material and methods. …”
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Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics by ChenDeng Lao, Wei Wei, JianWen Cheng, ShiJie Liao, XiaoLin Luo, Qian Huang, HengZhen Huang, JinMin Zhao

“…Three machine learning algorithms identified ATF3, CHKA, CLU, CTNNB1, and FASN as potential biomarkers. …”
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Machine learning-based identification of exosome-related biomarkers and drugs prediction in nasopharyngeal carcinoma by Zhengyu Wei, Guoli Wang, Yanghao Hu, Chongchang Zhou, Yuna Zhang, Yi Shen, Yaowen Wang

“…Results Through the application of three machine learning algorithms, five key genes (LTF, IDH1, ITGAV, CCL2, and LGALS3BP) were identified for the construction of a diagnostic model. …”
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Pain sensitisation and joint inflammation in patients with active rheumatoid arthritis by Sam Norton, Bruce W Kirkham, James Galloway, Khaldoun Chaabo, Toby Garrood, Zoe Rutter-Locher, Estee Chan, Alex Vincent

“…However clinical examination and PROMs did not reliably differentiate groups, emphasising PDUS remains an important tool.…”
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Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning by Kaiqi Cheng, Kaiqi Cheng, Jingzhe Xiao, Jingyuan He, Rongguang Yang, Jinjin Pei, Jinjin Pei, Wengang Jin, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

“…The 38 features selected by LASSO enabled clear differentiation of onion types via PCA, UMAP, and k-means clustering. …”
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A High Resolution Melting Analysis (HRM) PCR assay for the detection and identification of Old World Leishmania species. by Yusr Saadi-Ben Aoun, Hejer Souguir, Hamed Chouaieb, Mongia Kraiem, Insaf Bel Hadj Ali, Ahmed S Chakroun, Florian Noguier, Akila Fathallah-Mili, David Piquemal, Ikram Guizani

“…Its integration into molecular diagnostic algorithms for CL or in eco-epidemiological studies holds promise for improving disease management and control.…”
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Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification by Xiaojuan Cai, Ya Zhou, Jie Ren, Jinrong Wei, Shiyu Lu, Hanbing Gu, Weizhe Xu, Xun Zhu

“…ObjectiveAccurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. …”
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A prognostic glycolysis-related gene signature in osteosarcoma: implications for metabolic programming, immune microenvironment, and drug response by Naiqiang Zhu, Jingyi Hou, Yu Zhang, Ning Yang, KaiKai Ding, Chengbing Chang, Yanqi Liu, Haipeng Gu, Bin Chen, Xu Wei, Liguo Zhu

“…Using the non-negative matrix factorization (NMF) algorithm, patients with OS were stratified into distinct subgroups based on 288 GRGs identified through univariable Cox analysis. …”
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Association of microtubule-based processes gene expression with immune microenvironment and its predictive value for drug response in oestrogen receptor-positive breast cancer by Zhenfeng Huang, Minghui Zhang, Nana Zhang, Mengyao Zeng, Yao Qian, Meng Zhu, Xiangyan Meng, Ming Shan, Guoqiang Zhang, Feng Liu

“…Prognostic risk models were developed via random forest, support vector machines and the least absolute shrinkage and selection operator algorithm. Single-cell analysis revealed differences in the expression levels of key genes among various cell types. …”
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Direct Discrimination and Growth Estimation of Foodborne Bacteria in Raw Meat Using Electronic Nose by Wellington Belarmino Gonçalves, Wanderson Sirley Reis Teixeira, Aryele Nunes da Cruz Encide Sampaio, Otávio Augusto Martins, Evelyn Perez Cervantes, Mateus de Souza Ribeiro Mioni, Jonas Gruber, Juliano Gonçalves Pereira

“…The obtained data were evaluated by principal component analysis (PCA) and different machine learning algorithms. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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Exploring biomarkers and molecular mechanisms of Type 2 diabetes mellitus promotes colorectal cancer progression based on transcriptomics by Simin Luo, Yuhong Zhu, Zhanli Guo, Chuan Zheng, Xi Fu, Fengming You, Xueke Li

“…The relationship of key genes with immune cells and other cells was evaluated by immune infiltration algorithm and single-cell transcription analysis. …”
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Radiomics model building from multiparametric MRI to predict Ki-67 expression in patients with primary central nervous system lymphomas: a multicenter study by Yelong Shen, Siyu Wu, Yanan Wu, Chao Cui, Haiou Li, Shuang Yang, Xuejun Liu, Xingzhi Chen, Chencui Huang, Ximing Wang

“…And to assess the diagnostic performance of MRI radiomics-based machine-learning algorithms in differentiating the high proliferation and low proliferation groups of PCNSL. …”
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A radiomics approach for predicting gait freezing in Parkinson’s disease based on resting-state functional magnetic resonance imaging indices: A cross-sectional study by Miaoran Guo, Hu Liu, Long Gao, Hongmei Yu, Yan Ren, Yingmei Li, Huaguang Yang, Chenghao Cao, Guoguang Fan

“…Neurological and clinical characteristics were also evaluated. We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators. …”
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Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis by Ji Hui Fan, Xiao Min Li

“…GEO microarrays were used to identify differentially expressed mRNAs (DE-mRNAs) between CGN and healthy populations. …”
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