Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study by Zi-Tong Chen, Xiao-Long Li, Feng-Shan Jin, Yi-Lei Shi, Lei Zhang, Hao-Hao Yin, Yu-Li Zhu, Xin-Yi Tang, Xi-Yuan Lin, Bei-Lei Lu, Qun Wang, Li-Ping Sun, Xiao-Xiang Zhu, Li Qiu, Hui-Xiong Xu, Le-Hang Guo

“…By comprehensive comparison, we finally identified the optimal model (SARCO model) as the convenient solution. …”
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Circulating tumor DNA dynamics and recurrence risk in patients undergoing curative intent resection of colorectal cancer liver metastases: A prospective cohort study. by Jeanne Tie, Yuxuan Wang, Joshua Cohen, Lu Li, Wei Hong, Michael Christie, Hui Li Wong, Suzanne Kosmider, Rachel Wong, Benjamin Thomson, Julian Choi, Adrian Fox, Kathryn Field, Matthew Burge, Jenny Shannon, Dusan Kotasek, Niall C Tebbutt, Christos Karapetis, Craig Underhill, Andrew Haydon, Joy Schaeffer, Janine Ptak, Cristian Tomasetti, Nicholas Papadopoulos, Kenneth W Kinzler, Bert Vogelstein, Peter Gibbs

“…All 8 patients with persistently detectable ctDNA after adjuvant chemotherapy have recurred. …”
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Population-based colorectal cancer risk prediction using a SHAP-enhanced LightGBM model by Guinian Du, Hui Lv, Yishan Liang, Jingyue Zhang, Qiaoling Huang, Guiming Xie, Xian Wu, Hao Zeng, Lijuan Wu, Jianbo Ye, Wentan Xie, Xia Li, Yifan Sun

“…BackgroundColorectal cancer (CRC) is a highly frequent cancer worldwide, and early detection and risk stratification playing a critical role in reducing both incidence and mortality. we aimed to develop and validate a machine learning (ML) model using clinical data to improve CRC identification and prognostic evaluation.MethodsWe analyzed multicenter datasets comprising 676 CRC patients and 410 controls from Guigang City People’s Hospital (2020-2024) for model training/internal validation, with 463 patients from Laibin City People’s Hospital for external validation. …”
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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

“…Here, we developed and validated an interpretable machine learning (ML) model based on contrast-enhanced computed tomography (CECT) radiomics for preoperatively predicting PD-L1 expression status in patients with gastric cancer (GC). Methods We retrospectively recruited 285 GC patients who underwent CECT and PD-L1 detection from two medical centers. …”
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Non-Invasive Myocardial Work Identifies Patients with Obstructive Coronary Lesions After Orthotopic Heart Transplantation by Rebeca Manrique Antón, Marina Pascual Izco, Gorka Bastarrika, Agnés Díaz Dorronsoro, Ana Ezponda, Fátima de la Torre Carazo, Nahikari Salteráin, Leticia Jimeno-San Martín, Nerea Martín-Calvo, María Josefa Iribarren, Gregorio Rábago

“…If validated in larger studies, GWE could become a readily accessible tool for CAV detection.…”
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Evaluation of serum ESPL1 as a biomarker for early diagnosis of HBV-related hepatocellular carcinoma by Lu-Huai Feng, Lu Wei, Bobin Hu, Hengkai Liang, Qingmei Li, Qianbing Yin, Tumei Su, Long Huang, Hongqian Liang, Jianning Jiang, Jianning Jiang, Minghua Su, Minghua Su

“…Monitoring ESPL1 levels in serum could help with early detection and personalized screening HBV-HCC for individuals with chronic HBV infection.…”
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Construction and application of near-infrared spectroscopy analysis model for peanut quality traits by Hairong CAI, Wenjing SONG, Jianben LIN, Jiawei LIU, Yuanyuan GUO, Bowen LI, Haiyang YANG, Jiayi LU, Hanfeng SHI, Jiankuan WANG, Fangming LI, Tao GUO

“…The single and composite preprocessing methods were compared to select the best model that performed optimally under this spectral preprocessing by comparing the determination coefficients (R2) and root mean square errors of calibration (RMSEC) of different models. …”
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The proportion of endometrial tumours associated with Lynch syndrome (PETALS): A prospective cross-sectional study. by Neil A J Ryan, Raymond McMahon, Simon Tobi, Tristan Snowsill, Shona Esquibel, Andrew J Wallace, Sancha Bunstone, Naomi Bowers, Ioana E Mosneag, Sarah J Kitson, Helena O'Flynn, Neal C Ramchander, Vanitha N Sivalingam, Ian M Frayling, James Bolton, Rhona J McVey, D Gareth Evans, Emma J Crosbie

“…A growing consensus supports LS screening in EC; however, the expected proportion of test positives, and optimal testing strategy is uncertain. Previous studies from insurance-based healthcare systems were limited by narrow selection criteria, failure to apply reference standard tests consistently, and poor conversion to definitive testing. …”
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Predictive Value of Frailty, Comorbidity, and Patient-Reported Measures for Hospitalization or Death in Older Outpatients: Quality of Life and Depression as Prognostic Red Flags by Dimitrios Anagnostou, Nikolaos Theodorakis, Sofia Kalantzi, Aikaterini Spyridaki, Christos Chitas, Vassilis Milionis, Zoi Kollia, Michalitsa Christodoulou, Ioanna Nella, Aggeliki Spathara, Efi Gourzoulidou, Sofia Athinaiou, Gesthimani Triantafylli, Georgia Vamvakou, Maria Nikolaou

“…Future work should focus on developing or integrating screening tools with greater sensitivity to optimize early risk detection and guide preventive interventions.…”
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Identification of left atrial wall thickness in substrate mapping of atrial fibrillation by Wei Liu, Shijie Li, Shijie Li, Lina Dou, Chunai Hu, Bing Han

“…The regional segmentation method for left atrial voltage mapping was consistent with that used in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI). …”
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Hierarchical Event-Triggered Online Charging Management of Time-Varying Network of Electric Vehicles Based on Cooperative Game Theory by Maryam Amirabad Farahani, Mohammad Haeri

“…This article reports on a method for detecting disconnection between electric vehicle parking lots during charge management and uncertainties and how to deal with these issues. …”
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Development of a Test for the Real-time Fluorescence RNA Targeted Isothermal Amplification to Quickly Identify Cronobacter Species in Powdered Infant Formula by Ning Ding, Xiaona Tang, Fang Chen, Jiaqi Liang, Li Ling, Song Cheng, Lidan Ma, Yan Lu, Muyun Yuan, Jingwen Liu, Qing Liu, Wenrui Chen, Shan Huang, Furong Yang, Riqin Wu

“…The optimized SAT assay targeting 16s/23s rRNA was used to demonstrate the specificity, sensitivity of the detection assay. …”
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Global Transcriptome and Correlation Analysis Reveal Cultivar-Specific Molecular Signatures Associated with Fruit Development and Fatty Acid Determination in Camellia oleifera Abel by Shaofeng Peng, Jia Lu, Zhen Zhang, Li Ma, Caixia Liu, Yongzhong Chen

“…We attempt to identify genes related to fatty acid biosynthesis in an oil-tea Camellia seed kernel, generated a comprehensive transcriptome analysis of the seed kernel at different developmental stages, and explore optimal picking time of fruit. Material and Methods. …”
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Comparison of Collision Avoidance Algorithms for Unmanned Surface Vehicle Through Free-Running Test: Collision Risk Index, Artificial Potential Field, and Safety Zone by Jung-Hyeon Kim, Hyun-Jae Jo, Su-Rim Kim, Si-Woong Choi, Jong-Yong Park, Nakwan Kim

“…Noise within the data captured by the two-dimensional light detection and ranging system is filtered out using the k-dimensional tree and Euclidean distance methods, ensuring single obstacles are distinctly identified. …”
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Sex-specific ultrasound imaging biomarkers of neurodegeneration in a mouse model by Mark B. Russell, Drew P. Locke, Haley M. Adams, Alexander R. Pelley, Rojan Saghian, Rojan Saghian, Alexandre S. Maekawa, Darcie Stapleton, Grace V. Mercer, John G. Sled, John G. Sled, John G. Sled, Lindsay S. Cahill, Lindsay S. Cahill

“…IntroductionEarly detection of neurodegeneration is essential for optimizing interventions. …”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. …”
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Problems of interaction in the investigation of corruption crimes in the field of official activity and professional activity related to the provision of public services by Yu. K. Doroshenko

“…Cooperation in the investigation of crimes, in particular in the field of official activity, is one of the methods of combating crime, which consists in the coordination and combination in order and on the basis of the law, the efforts of several persons, divisions, bodies, etc. in order to ensure the optimization of the pre-trial investigation of criminal offenses. …”
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Leveraging artificial intelligence for diagnosis of children autism through facial expressions by Mahmood A. Mahmood, Leila Jamel, Nazik Alturki, Medhat A. Tawfeek

“…The ViT-ResNet152 model’s convolutional and transformer processing elements worked together to improve the accuracy of the diagnosis to 91.33% and make it better at finding different cases of autism spectrum disorder (ASD).The research outcomes demonstrate that AI tools show promise for delivering highly precise and standardized methods to detect ASD at an early stage. Future research needs to include multiple data types as well as extend dataset variability while optimizing hybrid architecture systems to elevate diagnostic forecasting. …”
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Convolutional kernel-based classification of industrial alarm floods by Gianluca Manca, Alexander Fay

“…The results show that our method outperforms two naive baselines and four existing AFC methods from the literature in terms of overall classification performance as well as the ability to optimize the balance between accurately identifying alarm floods from known classes and detecting alarm flood classes that have not been observed before.…”
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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…By eliminating irrelevant features, this approach could guide clinicians towards more accurate results and optimize diagnostic precision. Methods: This study included both patients with and without ovarian cancer, creating a dataset containing 50 independent variables/features. …”
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