The systemic oxidative stress index predicts clinical outcomes of esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy by Jifeng Feng, Jifeng Feng, Liang Wang, Xun Yang, Qixun Chen, Qixun Chen

“…It is yet unknown how SOS levels relate to the prognosis of esophageal squamous cell carcinoma (ESCC). The current research aims to explore the prognostic role of systemic oxidative stress index (SOSI) on ESCC receiving neoadjuvant immunochemotherapy (nICT).MethodsRetrospective recruitment was used to identify 224 nICT-treated ESCC patients. …”
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Ontological approach to modeling innovation processes on the example of a distributed educational network of the University by D. G. Korneev, M. S. Gasparian, A. A. Mikryukov

“…The key task of the current stage of the education system development is the task of transition to new methods of organization and support of the educational process, allowing providing high-quality training of graduates with practical knowledge and skills in demand in the labor market. …”
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Prognosis and immune landscape of bladder cancer can be predicted using a novel miRNA signature associated with cuproptosis by Zhilei Zhang, Fang Liu, Yongbo Yu, Fei Xie, Tao Zhu

“…We evaluated the tumor microenvironment (TME) of every patient using immune ESTIMATE, CIBERSORT, and ssGSEA algorithms. We also investigated the differences in tumor mutation burden (TMB) and drug sensitivity between two groups. …”
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Applications of machine learning for modeling and advanced control of crystallization processes: Developments and perspectives by Fernando Arrais R.D. Lima, Marcellus G.F. de Moraes, Amaro G. Barreto, Jr, Argimiro R. Secchi, Martha A. Grover, Maurício B. de Souza, Jr

“…Artificial intelligence techniques, such as machine learning (ML), are applied for modeling and controlling these processes. The current review aims to present the use of ML for modeling and advanced control of crystallization processes. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…By setting and validating upper and lower cut-offs corresponding to low, intermediate and high-risk disease, we improved risk stratification accuracy and reduced the proportion of patients needing ROR/Prosigna testing compared to current risk stratification. Conclusion: Machine learning algorithms can enhance patient selection for gene expression profiling, though further external validation is needed.…”
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Non‐Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning by Ruiyuan Weng, Yudian Xu, Xinjie Gao, Linlin Cao, Jiabin Su, Heng Yang, He Li, Chenhuan Ding, Jun Pu, Meng Zhang, Jiheng Hao, Wei Xu, Wei Ni, Kun Qian, Yuxiang Gu

“…Timely diagnosis and intervention can significantly reduce the risk of new‐onset stroke in patients with MMD. However, the current diagnostic methods are invasive and expensive, and non‐invasive diagnosis using biomarkers of MMD is rarely reported. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…Participants Participants had current low back pain without indicators of serious spinal pathology. …”
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A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images by Guannan Chen, Gaoqiang Liu, Xiaoqin Zhu, Mingyu Liu, Encai Zhang, Jichun Li, Kun Zhang, Lihang Lin

“…Texture features related to scar collagen second harmonic generation (SHG) images are useful for studying scars; however, current computational analysis methods require extensive computing resources. …”
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Deep MALDI-MS spatial omics guided by quantum cascade laser mid-infrared imaging microscopy by Lars Gruber, Stefan Schmidt, Thomas Enzlein, Huong Giang Vo, Tobias Bausbacher, James Lucas Cairns, Yasemin Ucal, Florian Keller, Martina Kerndl, Denis Abu Sammour, Omar Sharif, Gernot Schabbauer, Rüdiger Rudolf, Matthias Eckhardt, Stefania Alexandra Iakab, Laura Bindila, Carsten Hopf

“…Abstract In spatial’omics, highly confident molecular identifications are indispensable for the investigation of complex biology and for spatial biomarker discovery. However, current mass spectrometry imaging (MSI)-based spatial ‘omics must compromise between data acquisition speed and biochemical profiling depth. …”
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Study on the factors influencing the impaired abilities of daily living in middle-aged and older adult arthritis patients based on binary logistic regression and categorical decisi... by Bao-xuan Zhang, Bao-xuan Zhang, Bao-xuan Zhang, Jin-ping Luo, Jin-ping Luo, Jin-ping Luo, Jia-ying Sun, Jia-ying Sun, Jia-ying Sun, Ming-hui Geng, Ming-hui Geng, Ming-hui Geng, Yi-fan Mou, Yi-fan Mou, Yi-fan Mou, Nan-nan Cheng, Nan-nan Cheng, Nan-nan Cheng, Zhao-xuan Wang, Zhao-xuan Wang, Zhao-xuan Wang, Wen-qiang Yin, Wen-qiang Yin, Wen-qiang Yin, Zhong-ming Chen, Zhong-ming Chen, Zhong-ming Chen, Dong-ping Ma, Dong-ping Ma, Dong-ping Ma

“…BackgroundArthritis is the most disabling disease worldwide, and the presence of the disease usually greatly threatens the patient’s activities of daily living (ADL). Currently, there are a few studies that are related to exploring factors associated with impaired ADL in middle-aged and older adult arthritis patients. …”
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Serum metabolic fingerprints encode functional biomarkers for ovarian cancer diagnosis: a large-scale cohort studyResearch in context by Wanshan Liu, Xiaoxiao Hu, Zhouzhou Bao, Yanyan Li, Juxiang Zhang, Shouzhi Yang, Yida Huang, Ruimin Wang, Jiao Wu, Xiaoyu Xu, Qi Sang, Wen Di, Huaiwu Lu, Xia Yin, Kun Qian

“…Summary: Background: Ovarian cancer (OC) ranks as the most lethal gynaecological malignancy worldwide, with early diagnosis being crucial yet challenging. Current diagnostic methods like transvaginal ultrasound and blood biomarkers show limited sensitivity/specificity. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

“…Predicting which patients will experience BCR in advance helps in formulating more targeted prostatectomy procedures. However, current preoperative recurrence prediction mainly relies on the use of the Gleason grading system, which omits within-grade morphological patterns and subtle histopathological features, leaving a significant amount of prognostic potential unexplored. …”
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Enhancing Detection of Multi-Frequency-Modulated SSVEP Using Phase Difference Constrained Canonical Correlation Analysis by Chi Man Wong, Ze Wang, Boyu Wang, Agostinho Rosa, Tzyy-Ping Jung, Feng Wan

“…However, the existing calibration-free recognition algorithms based on the traditional canonical correlation analysis (CCA) cannot provide the merited performance. …”
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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…Consequently, there is an urgent need to systematically assess the current progress in anti-money laundering (AML) research, anticipate future directions in blockchain-based AML technologies, and develop effective countermeasures to mitigate the evolving financial security challenges associated with blockchain applications. …”
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A Novel Forest Dynamic Growth Visualization Method by Incorporating Spatial Structural Parameters Based on Convolutional Neural Network by Linlong Wang, Huaiqing Zhang, Kexin Lei, Tingdong Yang, Jing Zhang, Zeyu Cui, Rurao Fu, Hongyan Yu, Baowei Zhao, Xianyin Wang

“…Current visual methods of forest dynamic growth mostly focus on the plot or stand level, which cannot express the morphological and structural characteristics of individual trees, as well as their statistical linkages, and causes each tree in the stand to grow at the same rate. …”
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Clinical Manifestation and Errors in the Diagnosis of Classical Paroxysmal Nocturnal Hemoglobinuria: A clinical case series of 150 patients by AD Kulagin, OU Klimova, AV Dobronravov, MO Ivanova, TA Rudakova, EV Babenko, VA Dobronravov, BV Afanas’ev

“…The results of the research showed the need for multidisciplinary approach and strict adherence to diagnostic algorithms of PNH in the risk groups, according to current recommendations.…”
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Soil Moisture Retrieval in Winter Wheat Fields at Different Growth Stages: Integrating a Two-Component Polarimetric SAR Decomposition With CIEM by Wenxin Xue, Qinghua Xie, Xing Peng, J. David Ballester-Berman, Jinfei Wang, Jiali Shang, Haiqiang Fu, Jianjun Zhu

“…This article contributes to the current body of the literature on radar-driven SM retrieval approaches by proposing an integrated <italic>C</italic>-band two-component polarimetric decomposition method applied on winter wheat fields. …”
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Deep Multi-Modal Skin-Imaging-Based Information-Switching Network for Skin Lesion Recognition by Yingzhe Yu, Huiqiong Jia, Li Zhang, Suling Xu, Xiaoxia Zhu, Jiucun Wang, Fangfang Wang, Lianyi Han, Haoqiang Jiang, Qiongyan Zhou, Chao Xin

“…The diagnostic potential of recent multi-modal skin lesion detection algorithms is limited because they ignore dynamic interactions and information sharing across modalities at various feature scales. …”
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Exploring the relationship between dietary patterns and health-related quality of life among Iranian adult population: Tehran lipid and glucose study by Mahdieh Niknam, Somayeh Hosseinpour-Niazi, Sara Jalali-Farahani, Parisa Amiri, Parvin Mirmiran, Firoozeh Hosseini-Esfahani, Elaheh Ainy, Fereidoun Azizi

“…Abstract Background The current study aims to investigate the association between dietary patterns and health-related quality of life (HRQoL) in a large Iranian adult population. …”
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