SEARCH FOR CLINICAL PREDICTORS OF PULMONARY HYPERTENSION IN PATIENTS WITH SYSTEMIC SCLEROSIS by N. A. Klyaus, M. A. Simakova, A. L. Maslyansky, O. M. Moiseeva

“…The scope of investigations necessary to detect PH, the complexity of its diagnostic algorithms for routine use, as well as the impossibility to apply the existing algorithms for all PH variants increase the relevance of searching for novel PH predictors in patients with SSc.Objective: to reveal the relationship of capillary structural changes to the clinical and immunological subtype of SSc, disease activity, and risk for PH.Subjects and methods. …”
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Teaching Internal Medicine Residents to Critically Appraise the Role of Race in Pulmonary Function Testing by Ananya Bhatia-Lin, Nirav Bhakta, Neha Deshpande, Laura Granados, Rosemary Adamson

“…We conducted pre- and posttest surveys; the posttest survey was designed using the Kirkpatrick model to assess reaction, learning, and anticipated behavioral change. Mean score differences were evaluated for level 2 questions using Cohen's d effect size. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…We present a systematic review of 17 mainstream light field spatial super-resolution techniques, evaluating their performance across seven public datasets. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…GMM assigns data points probabilistically, assuming data are generated from a mixture of Gaussian distributions, while AP identifies clusters by finding representative exemplars without needing a predefined number of clusters. To evaluate the performance of these clustering algorithms, we assigned the clusters into six classes based on vegetation growth patterns observed over the five-year period. …”
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Incidence of Rapid Rate Non‐Sustained and Sustained Ventricular Tachycardia in Implantable Cardioverter‐Defibrillator Recipients and Its Correlation With Heart Failure Guideline‐Di... by Muhammad Taha Khan, Ghazala Irfan, Sarim Ansari, Zubair Mumtaz, Faisal Qadir, Azam Shafquat

“…Rapid rate non‐sustained ventricular tachycardia (RR‐NSVT) and sustained ventricular tachycardia (VT) can be detected on implantable cardioverter‐defibrillator (ICD) interrogation due to discrimination algorithms that differentiate supra‐ventricular from ventricular tachycardia. …”
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Oxidative stress gene expression in ulcerative colitis: implications for colon cancer biomarker discovery by Ting Yan, Ting Su, Miaomiao Zhu, Qiyuan Qing, Binjie Huang, Jun Liu, Tenghui Ma

“…We downloaded datasets from public repositories and conducted gene set enrichment analysis (GSEA), screening for oxidative stress-related differentially expressed genes (OXSRDEGs) to evaluate their diagnostic potential. …”
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Exploring the role of hepsin in prostate cancer: bioinformatics, molecular Docking and molecular dynamics simulations by Hongying Peng, Dan Du, Zhonggui Hu, Zhiliang Xia

“…Using advanced computational techniques such as weighted gene co-expression network analysis (WGCNA), Lasso regression, and random forest algorithms, we pinpointed key genes involved in tumorigenesis. …”
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Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground‐Glass Nodules Based on AI‐Extracted Radiomic Features by Guozhen Yang, Yuanheng Huang, Huiguo Chen, Weibin Wu, Yonghui Wu, Kai Zhang, Xiaojun Li, Jiannan Xu, Jian Zhang

“…Nineteen radiomic features were extracted and filtered using Boruta and LASSO algorithms. Seven ML classifiers were evaluated using AUC‐ROC, decision curve analysis (DCA), and SHAP interpretability. …”
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Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer by Miao Ao, You Wu, Kunyu Wang, Haixia Luo, Wei Mao, Anqi Zhao, Xiaomeng Su, Yan Song, Bin Li

“…Methods RNA expression profiles and single-cell data were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus databases for screening and validating mitochondria-related differentially expressed genes (DEGs). After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. …”
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A Machine Learning Approach for Predicting Maternal Health Risks in Lower-Middle-Income Countries Using Sparse Data and Vital Signs by Avnish Malde, Vishnunarayan Girishan Prabhu, Dishant Banga, Michael Hsieh, Chaithanya Renduchintala, Ronald Pirrallo

“…The models’ performance were evaluated using regular, random and stratified sampling techniques. …”
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Towards sustainable agriculture in Iran using a machine learning-driven crop mapping framework by Iman Khosravi

“…The Ministry of Agriculture-Jihad (MAJ) and the Iranian Space Agency (ISA) aim to accurately estimate the cultivated area of strategic crops and evaluate their annual yield through meticulous crop mapping. …”
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From Words to Ratings: Machine Learning and NLP for Wine Reviews by Iliana Ilieva, Margarita Terziyska, Teofana Dimitrova

“…The descriptions were transformed into numerical representations using a pre-trained language model (BERT), after which algorithms were used to predict style categories and ratings. …”
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Investigating Similarities Across Decentralized Finance (DeFi) Services by Junliang Luo, Stefan Kitzler, Pietro Saggese

“… We explore the adoption of graph representation learning (GRL) algorithms to investigate similarities across services offered by Decentralized Finance (DeFi) protocols. …”
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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…Biomarkers were extracted from two dementia cohorts (4356 vol, 162 233 images) and one vascular disease cohort (869 vol, 42 850 images) using deep learning-based segmentation algorithms designed specifically for FLAIR. Biomarkers from all cohorts were summarized using descriptive statistics, correlation analysis, and ANCOVA to assess differences in diagnostic labels while accounting for demographic and acquisition factors. …”
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Lossy DICOM conversion may affect AI performance by Robin Sebastian Mayer, Fabian Fliedner, Ingvild Frøberg Mathisen, Anna Laib, Julia Bein, Marco Eichelberg, Peter J. Wild, Nadine Flinner

“…So, if DICOM images are intended for a diagnostic use, all processes and algorithms must be (re-)evaluated with the converted files, as images are not identical. …”
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Transbronchial lung cryobiopsy for diagnosing interstitial lung disease: a cross-sectional, comparative study by Min Yu, Xuefeng Xu, Xiaoyan Xin, Shangwen Yang, Yihua Wang, Yonglong Xiao, Shenyun Shi, Xuebing Feng

“…Conclusions This study indicated that the clinical applicability of TBLC in ILD diagnostic algorithms, with a diagnostic yield of 85.0% and an acceptable safety profile.…”
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Integrating machine learning with mendelian randomization for unveiling causal gene networks in glioblastoma multiforme by Lixin Du, Pan Wang, Xiaoting Qiu, Zhigang Li, Jianlan Ma, Pengfei Chen

“…Methods This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM. …”
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Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics by Zhenyu Wang, Chaojun Jiang, Xianxian Zhang, Tianchi Mu, Qingqing Li, Shu Wang, Congsong Dong, Yuan Shen, Zhenyu Dai, Fei Chen

“…Additionally, no significant differences were observed between the combined radiomics models and the clinical models across the five algorithms. …”
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The potential crosstalk genes and molecular mechanisms between systemic lupus erythematosus and periodontitis by Kai Zhao, Xiaolong Li, Qingmiao Zhu, Mengyu Zhu, Jinge Huang, Ting Zhao

“…Receiver operating characteristic (ROC) curves were generated using a new validation dataset to evaluate the performance of candidate genes. Finally, levels of immune cell infiltration in SLE and PD were assessed using CIBERSORTx.ResultsA total of 50 core genes were identified between the genes screened by WGCNA and DEGs. …”
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Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

“…A study was conducted to examine differentially expressed genes (DEGs) in healthy individuals and patients diagnosed with CS and AS. …”
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