Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

“…The dataset was divided into training and test set with a ratio of 7:3 with 6 machine learning algorithms implemented to diagnosis pleural effusion. …”
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Diagnosis on Ultrasound Images for Developmental Dysplasia of the Hip with a Deep Learning-Based Model Focusing on Signal Heterogeneity in the Bone Region by Hirokazu Shimizu, Ken Enda, Hidenori Koyano, Takuya Ogawa, Daisuke Takahashi, Shinya Tanaka, Norimasa Iwasaki, Tomohiro Shimizu

“…Existing automatic diagnostic models lack precision due to noise, but 3D technology may enhance it. This study aimed to create and assess a deep-learning-based model for automated DDH diagnosis by using 3D transformation technology on two-dimensional ultrasound images. …”
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Thermal ablation in the management of oligometastatic colorectal cancer by Thierry De Baere, Lambros Tselikas, Alexandre Delpla, Charles Roux, Eloi Varin, Adrian Kobe, Steven Yevich, Frederic Deschamps

“…As ablation techniques and technology improve, the role of percutaneous thermal ablation may expand even into surgically resectable disease. …”
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Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis by Marcos Uceta, Alberto del Cerro‐León, Danylyna Shpakivska‐Bilán, Luis M. García‐Moreno, Fernando Maestú, Luis Fernando Antón‐Toro

“…Recent studies have changed their scope into finding predisposition factors that may lead adolescents into this kind of patterns of consumption. …”
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Pan-Cancer Analysis of Disulfidptosis-Related Genes Affecting Prognosis and Tumor Microenvironment by Jingyang SUN, Rongxuan JIANG, Liren HOU, Huanhuan DONG, Yihan LIN, Niuniu DONG, Guangjian ZHANG, Yanpeng ZHANG

“…ConclusionPan-cancer analysis of DRGs indicates that DRGs may serve as important biomarkers for the diagnosis and prognosis of renal clear-cell carcinoma, lung adenocarcinoma, and hepatocellular carcinoma.…”
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Applications of molecular dynamics in nanomaterial design and characterization - A review by Md. Aminul Islam, S M Maksudur Rahman, Juhi Jannat Mim, Safiullah Khan, Fardin Khan, Md. Ahadul Islam Patwary, Nayem Hossain

“…Recent advances, such as improved multiscale modeling and computational algorithms and real-time simulations, shed light onto MD processes of revolutionizing nanotechnology. …”
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Two-dimensional differential form of distributed Xinanjiang model by J. Zhao, Z. Liang, V. P. Singh, V. P. Singh, V. P. Singh, T. Wen, Y. Hu, B. Li, J. Wang

“…Our results suggested that (a) numerical errors in the existing distributed Xinanjiang model are significant and may be exacerbated by a potential terrain amplification effect, which could be effectively controlled by the fully coupled numerical framework within the TDD-XAJ model; (b) the 2D slope concentration methods showed enhanced terrain capture ability and eliminated the reliance on the flow direction algorithms used in 1D methods; and (c) the TDD-XAJ model exhibited improved simulation capabilities compared to the existing model when applied in the Tunxi watershed, particularly for flood volume. …”
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THE EFFECTS OF LIQUIRITIGEN ON THE LUKEMIA INHIBITORY FACTOR RECEPTOR IN GRANULOSA CELLS OF INFERTILE PATIENTS by Emel Usta, Sibel Köktürk, Sibel Doğan, Ayşe Altun, Sibel Bulgurcuoğlu Kuran, Feride Özdemir

“…These results suggest that LQ may be used as an alternative medium agent in IVF units. …”
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Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

“…These genes were downregulated in the middle temporal gyrus of patients with Alzheimer’s disease and may be used to target the VEGF pathway. Alzheimer’s disease mouse models demonstrated consistent altered expression of these genes in the middle temporal gyrus. …”
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Multi-omics and experimental validation studies reveal key biomarkers of cellular senescence in diabetic retinopathy by Jinju Li, Hao Yang, Yixuan Lin, Zhaohui Fang

“…Thus, investigating these genes may provide new therapeutic targets for DR treatment by targeting cellular senescence.…”
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The Effect of Hearing Aid Amplification on Gait Parameters: A Pilot Study Using Ear-Worn Motion Sensors by Ann-Kristin Seifer, Arne Küderle, Kaja Strobel, Ronny Hannemann, Björn M. Eskofier

“…Prior research suggests that hearing aids may improve balance; however, their impact on gait remains less well explored. …”
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Using machine learning to predict the rupture risk of multiple intracranial aneurysms by Junqiang Feng, Chunyi Wang, Yu Wang, He Liu, He Liu

“…Error analysis revealed that the model’s lower TPR may be attributed to the small sample size and dataset imbalance. …”
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Impact of monitor unit optimization in volumetric modulated arc therapy planning for nasopharyngeal carcinoma. by Huaqu Zeng, Zhen Li, Zongyou Chen, Shukui Tang, Qifu Lin, Minzhi Zhong, Zunbei Wen

“…Dual-arc VMAT plan were designed using photon optimization algorithms without the monitor unit objective (MUO) tool, denoted as the base plan. …”
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Association of Obesity with Forearm Fractures, Bone Mineral Density and Fracture Risk (FRAX®) During Postmenopausal Period by Erkan Mesci, Nilgün Mesci, Afitap İçağasıoğlu, Ercan Madenci

“…It should be kept in mind that obesity may not necessarily be protective against fractures and treatment algorithms based solely on BMD might be inadequate to predict future fracture risk.…”
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How Do Ethical Factors Affect User Trust and Adoption Intentions of AI-Generated Content Tools? Evidence from a Risk-Trust Perspective by Tao Yu, Yihuan Tian, Yihui Chen, Yang Huang, Younghwan Pan, Wansok Jang

“…Through a systematic literature review and expert interviews, eight core ethical dimensions were identified: Misinformation (MIS), Accountability (ACC), Algorithmic Bias (ALB), Creativity Ethics (CRE), Privacy (PRI), Job Displacement (JOD), Ethical Transparency (ETR), and Control over AI (CON). …”
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Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study by Mengdie Liu, Wen Guo, Jin Peng, Jinhui Wu

“…BackgroundSarcopenia (SP) is a progressive, age-related disease that may result in various adverse health outcomes and even mortality in older adults. …”
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Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews by Miehleketo Mathebula, Abiodun Modupe, Vukosi Marivate

“…Supervised learning algorithms have been popularly employed for this task, but the performance of these models has been compromised due to the brevity of the content and the presence of idiomatic expressions, sound imitations, and abbreviations. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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A Soft Sensor Based Inference Engine for Water Quality Assessment and Prediction by Micheal A Ogundero, Theophilus A Fashanu, Foluso O Agunbiade, Kehinde Orolu, Ahmed A Yinusa, Usman A Daudu, Muhammed O H Amuda

“…Toxic contaminants with potential exposure to health risks now appear in urban drainage systems. These contaminants may be measured in specific concentrations or gross terms with impact on potential of hydrogen (pH) and dissolve oxygen (DO). …”
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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer by Erha Munai, Siwei Zeng, Ze Yuan, Dingyi Yang, Yong Jiang, Qiang Wang, Yongzhong Wu, Yunyun Zhang, Dan Tao

“…Four different machine learning (ML) algorithms were used to create prediction models for BMs in ES-SCLC patients. …”
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