Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

“…Abstract Background Thyroid cancer (THCA) exhibits high molecular heterogeneity, posing challenges for precise prognosis and personalized therapy. Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value. …”
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How we treat polycythemia vera by V. A. Shuvaev, I. S. Martynkevich

“…The discovery of the pathogenetic role of mutations in the Janus kinase II gene has led to the possibility of establishing a diagnosis based not only on morphology, but also on genetic verification and to the development of directed targeted therapy, which is much more effective than previously used methods. The introduction of molecular genetic screening led to the need for a differential diagnosis with familial erythrocytosis, and the lessons of the coronavirus pandemic revealed the presence in the population of a significant proportion of patients with erythrocytosis due to the carriage of gene polymorphisms associated with familial hemochromatosis. …”
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Diagnosing facial synkinesis using artificial intelligence to advance facial palsy care by Leonard Knoedler, Christian Festbaum, Jillian Dean, Helena Baecher, Grégoire de Lambertye, Maximilian Maul, Thomas Schaschinger, Tobias Niederegger, Alexandra Scheiflinger, Michael Alfertshofer, Khalil Sherwani, Claudius Steffen, Max Heiland, Steffen Koerdt, Samuel Knoedler, Andreas Kehrer

“…This study aimed to develop a cost-effective, rapid, and accurate artificial intelligence (AI)-based algorithm to screen FP patients for facial synkinesis. …”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…Applying this model to seed lot screening increased the proportion of high-quality seeds from 47.7 % to 93.4 %. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
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Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system. by Chaoyang Zhao, Huilin Li, Ziyou Yuan, Zihan Yang, Tiantian Wang, Yan Wang, Qian Tong, Shaofeng Hao

“…The findings aim to provide a scientific basis for the prevention, early screening, and formulation of personalized treatment strategies for myopia.…”
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Callback time preference for prescreening visits among Black residents in the Boston area: findings from two randomized controlled trials by Ruth Zeto, Oluwagbemisola Ibikunle, Jingyi Cao, Hannah Col, Dhrumil Patil, Ruth-Alma Turkson-Ocran, Mingyu Zhang, Timothy B. Plante, Stephen P. Juraschek

“…Staff call attempts and participant screening status were logged prospectively. Gender was estimated based on first name, using a published algorithm. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Moreover, the performance of these algorithms is hampered by the scarcity of large‐scale, high‐quality annotated data. …”
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LncRNAs regulates cell death in osteosarcoma by Ping’an Zou, Zhiwei Tao, Zhengxu Yang, Tao Xiong, Zhi Deng, Qincan Chen, Li Niu

“…Three machine learning algorithms—Support Vector Machine, Random Forest, and Generalized Linear Model—were utilized to select feature genes. …”
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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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Identification of anoikis-related genes classification patterns and immune infiltration characterization in chronic rhinosinusitis with nasal polyps based on machine learning by Ziqi Chen, Lingmei Qu, Qing Hao, Shuang Teng, Shuo Liu, Qin Wu, Hongtian Yi, Xianji Shen, Liang Li, Zhaonan Xu, Yanan Sun

“…Immune cell infiltration was analysed using the CIBERSORT algorithm. CRSwNP samples were classified via consensus clustering. …”
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Identification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study by Na Wang, Yujia Chen, Jianli Lin, Yulan Lin, Haoyuan Song, Weihai Huang, Liling Shen, Fa Chen, Fengqiong Liu, Jing Wang, Yu Qiu, Bin Shi, Ling Li, Lisong Lin, Lizhen Pan, Baochang He

“…The disease classification model, constructed using a KNN algorithm with 13 metabolites selected through LASSO screening, achieved the best performance, with an AUC of 0.978 (0.955-1.000). …”
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A study on early diagnosis for fracture non-union prediction using deep learning and bone morphometric parameters by Hui Yu, Qiyue Mu, Zhi Wang, Yu Guo, Jing Zhao, Guangpu Wang, Qingsong Wang, Xianghong Meng, Xiaoman Dong, Shuo Wang, Jinglai Sun

“…This study aims to create a fracture micro-CT image dataset, design a deep learning algorithm for fracture segmentation, and develop an early diagnosis model for fracture non-union.MethodsUsing fracture animal models, micro-CT images from 12 rats at various healing stages (days 1, 7, 14, 21, 28, and 35) were analyzed. …”
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Numerical analysis method of stress wave transmission attenuation of coal and rock structural plane by Wenlong SHEN, Renren ZHU, Ziqiang CHEN, Guocang SHI

“…The simulation and machine learning of stress wave transmission in the experimental process of Split Hopkinson Pressure Bar (SHPB) were carried out by combining the Barton-Bandis nodal ontology model, UDEC discrete element simulation and Gray Wolf Algorithm optimized BP neural network technology. …”
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Sleepiness, fatigue, anxiety and depression in Chronic Obstructive Pulmonary Disease and Obstructive Sleep Apnea - Overlap - Syndrome, before and after continuous positive airways... by Nicholas-Tiberio Economou, Ioannis Ilias, Lemonia Velentza, Yiannis Papachatzakis, Paul Zarogoulidis, Anastasios Kallianos, Georgia Trakada

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Bioinformatics analysis of potential targets influencing the prognosis of OSCC by ZOU Xian, SONG Tao

“…The Timer website was used to analyze the relationship between hub genes and immune cell infiltration and immune checkpoints. Based on Lasso-Cox algorithm, a prognostic risk model of related genes was constructed. …”
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FDTooth: Intraoral Photographs and CBCT Images for Fenestration and Dehiscence Detection by Keyuan Liu, Marawan Elbatel, Guang Chu, Zhiyi Shan, Fung Hou Kumoi Mineaki Howard Sum, Kuo Feng Hung, Chengfei Zhang, Xiaomeng Li, Yanqi Yang

“…The developed dataset and model can serve as valuable resources for research on interdisciplinary dental diagnostics, offering clinicians a non-invasive, efficient method for early FD screening without invasive procedures.…”
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Leveraging advanced technologies for early detection and diagnosis of oral cancer: Warning alarm by Saantosh Saravanan, N. Aravindha Babu, Lakshmi T, Mukesh Kumar Dharmalingam Jothinathan

“…Specialized algorithms such as the Recombination-Based Improved Population Optimization Parallel Covariance Matrix Adaptation Evolution Strategy (RB-IPOP CMA-ES) allow for better accuracy of deep learning models, as this enhances the performance of developing models for early diagnosis of oral cancer. …”
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Analyzing adjustment and verification errors in electric metering devices for smart power systems considering multiple environmental factors by Chuanliang He, Xin Xia, Bo Zhang, Wei Kang, Jinxia Zhang, Haipeng Chen

“…Then, an error adjustment model based on gated recurrent unit-attention is constructed, and the particle swarm optimization algorithm is adopted for the purpose of optimizing hyperparameters. …”
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The clinical utility and safety of biomarker-guided immunosuppression withdrawal in liver transplantation: the LIFT prospective RCT by Julien Vionnet, Rosa Miquel, Juan G Abraldes, Juan-Jose Lozano, Pablo Ruiz, Miquel Navasa, Aileen Marshall, Frederik Nevens, William Gelson, Joanna Leithead, Steven Masson, Elmar Jaeckel, Richard Taubert, Phaedra Tachtatzis, Dennis Eurich, Kenneth Simpson, Eliano Bonaccorsi-Riani, James Ferguson, Alberto Quaglia, Maria Elstad, Marc Delord, Abdel Douiri, Alberto Sánchez-Fueyo

“…This was done by enrolling patients more than 3 years after transplantation and allocating them at random to two groups. …”
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