Tumor-specific PET tracer imaging and contrast-enhanced Mri based tumor volume differences inspection of glioblastoma patients by Irshad Ahmed Abbasi, Mohammed Alshehri, Yahya AlQahtani

“…These methods encompassed adaptive threshold algorithms, batch processing pipelines, and image attribute extraction algorithms. …”
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ABDOMINAL HEMORRHAGE IN CASE OF CATATRAUMA by A. M. Khadzhibaev, P. K. Sultanov

“…The results of diagnostic and treatment were analyzed in 111 victims with abdominal multitrauma at the period from 2010 to 2013. …”
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Exploring the multifaceted roles of glutamate oxaloacetate transaminase 1 as a biomarker and therapeutic target in colorectal cancer and pan-cancer analyses by Xi Wang, Longquan Pi, Yuning Chen, Jiangyu Tan, Yingying Wang, Kaiyan Xia, Xianchun Zhou

“…Abstract Colorectal cancer (CRC) is a global health issue requiring novel diagnostic and therapeutic approaches to improve patient outcomes. …”
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DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE by Vladimir I. Freyman

“…Basic data and a detailed step-by-step implementation phase of the proposed common iterative approach to the development of disciplinary competence testable component structure are considered. Tests and diagnostic tables for different options of designing are proposed. …”
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Comparing FIB-4, VCTE, pSWE, 2D-SWE, and MRE Thresholds and Diagnostic Accuracies for Detecting Hepatic Fibrosis in Patients with MASLD: A Systematic Review and Meta-Analysis by Mitchell Patrick Wilson, Ranjit Singh, Shyam Mehta, Mohammad Hassan Murad, Christopher Fung, Gavin Low

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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

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Characteristic genes and immune infiltration analysis of gastric cancer based on bioinformatics analysis and machine learning by Chengwei Xia, Yini Liu, Xin Qing

“…Finally, BANF1, DUSP14, and VMP1 were regarded as key biomarkers in GC patients based on the overlapping genes that we found, and these three biomarkers demonstrated great diagnostic significance. Additionally, the hub biomarkers had different levels of association with macrophages, neutrophils, memory B cells, and plasma cells. …”
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Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study by Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah

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Diagnosis of Pain Deception Using Minnesota Multiphasic Personality Inventory-2 Based on XGBoost Machine Learning Algorithm: A Single-Blinded Randomized Controlled Trial by Hyewon Chung, Kihwan Nam, Subin Lee, Ami Woo, Joongbaek Kim, Eunhye Park, Hosik Moon

“…The main goal of this study was to evaluate the diagnostic value of pain deception using machine learning (ML) analysis with the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) scales, considering accuracy, precision, recall, and f1-score as diagnostic parameters. …”
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Scoring of swine lung images: a comparison between a computer vision system and human evaluators by Robert Valeris-Chacin, Beatriz Garcia-Morante, Marina Sibila, Albert Canturri, Isaac Ballarà Rodriguez, Ignacio Bernal Orozco, Ramon Jordà Casadevall, Pedro Muñoz, Maria Pieters

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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

“…The starting point is an adaptive algorithm that performs a dynamic tolerance band formation based on different criteria, emphasizing on adaptive characteristic segmentation. …”
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A two‐stage transformer fault diagnosis method based multi‐filter interactive feature selection integrated adaptive sparrow algorithm optimised support vector machine by Hanyu Shi, Mingxia Chen

“…Finally, Experiments were conducted using real fault data, and the diagnostic performance of different feature inputs, optimisation algorithms and classifiers were compared. …”
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EVALUATION OF THE EFFECTIVENESS OF A NONSTEROIDAL ANTI-INFLAMMATORY DRUG (NSAID) SELECTION ALGORITHM BASED ON THE ANALYSIS OF RISK FACTORS FOR DRUG-INDUCED COMPLICATIONS IN REAL CL... by A. E. Karateev, A. M. Lila, M. V. Churyukanov, K. V. Skorobogatykh, A. V. Amelin, D. V. Zakharov, E. A. Trofimov, V. A. Shirokov, T. V. Popova, E. A. Shestel, Z. A. Goncharova, A. I. Kulikov, O. B. Nesmeyanova, M. V. Galikhanova

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Driving Cycle for Passenger Cars on Urban Roads in Pristina, Kosovo by Flamur Salihu, Yusuf Kağan Demir

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An interpretable machine learning method for fault diagnosis of oil-immersed transformers based on edge inference by Dong Hu, Yong Yang, Hao Dai, Chao Tang, Jufang Xie

“…Following edge-end inference, the SHapley Additive exPlanations method is employed to analyze feature impact on diagnostic results, visualizing the significance of different characteristic gases for fault types using SHAP values. …”
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A KNN-based model for non-invasive prediction of hemorrhagic shock severity in prehospital settings: integrating MAP, PBUCO2, PTCO2, and PPV by Peng Zhao, Wencai Pan, Xin Zou, Jiaqing Yang, Shihui Zhang, Yufei Liu, Yang Li

“…Current non-invasive single-parameter monitoring shows limited diagnostic reliability. We developed a multi-parameter predictive model integrating mean arterial pressure (MAP), buccal mucosal CO₂ (PBUCO₂), transcutaneous oxygen (PTCO₂), and pulse pressure variation (PPV). using K-nearest neighbors (KNN) algorithm. …”
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AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification—Decoding Lateral Epicondylitis in Forearm Muscles by Mehdi Shirzadi, Mónica Rojas Martínez, Joan Francesc Alonso, Leidy Yanet Serna, Joaquim Chaler, Miguel Angel Mañanas, Hamid Reza Marateb

“…Background: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. …”
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Decoding survival in MASLD: the dominant role of metabolic factors by Zhiqiang Jin, Cheng Zeng, Yang Yang, Shan Zhong, Zhi Zhou

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Integration of Microarray Data and Single-Cell Sequencing Analysis to Explore Key Genes Associated with Macrophage Infiltration in Heart Failure by Rao J, Wang X, Wang Z

“…Additionally, we employed four integrated machine learning algorithms to identify macrophage-related genes with diagnostic value, and in vivo validation was performed. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

“…Despite performing well in almost all of the metrics, SGD’s low recall score shows that it is not the most optimal algorithm. Given that recall score is prioritized in the context of clinical diagnostics, Random Forest emerges as a strong candidate due to its balanced performance across key metrics.…”
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