Immunotyping of thyroid cancer for clinical outcomes and implications by Jin Xu, Zhen Luo, Dayong Xu, Mujing Ke, Cheng Tan

“…Univariate Cox analysis was performed to screen prognostic genes and THCA samples were categorized into different immune cell-related clusters. …”
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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study by Shengyu Liu, Anran Wang, Xiaolei Xiu, Ming Zhong, Sizhu Wu

“…The macrofactors affecting model performance were also screened using the multilevel factor elimination algorithm. …”
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Leveraging diverse cell-death patterns to predict to predict prognosis and immunotherapy in hepatocellular carcinoma by Xiaoxiang Zhang, Dongxiao Ding, Dianqian Wang, Yunsheng Qin

“…Although many efforts have been made to improve the prognosis of LIHC, the situation is still dismal. …”
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The Marine Safety Simulation based Electronic Chart Display and Information System by Xin Yu Zhang, Yong Yin, Jin YiCheng, XiaoFeng Sun, Ren HongXiang

“…The man-machine conversation method is taken to amend planned route to obtain autodeciding of feasibility according to ECDIS information, and the route monitoring algorithm is improved by enhancing its precision caused by screen coordinate conversion. …”
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CALCULATION OF OBJECTS THERMAL IMAGING PARAMETERS FROM UNMANNED AERIAL VEHICLES by L. V. Katkovsky

“…Analytical formulas for estimating the minimum resolvable temperature difference are obtained on the basis of a mathematical model of the thermal imager as a linear system of individual components based on the technique that differs from the generally accepted one. Estimates were made for two cases: observation of a thermal image by an operator on a display screen and for the case when an electronic image is analyzed by a threshold algorithm with no operator engaged. …”
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Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study by Jaclyn A Pagliaro, Lauren K Wash, Ka Ly, Jenny Mathew, Alison Leibowitz, Ryan Cabrera, Jolie B Wormwood, Varsha G Vimalananda

“…ResultsOf the 7714 who were mailed a study invitation, 560 were screened. Of the screened patients, 203 were enrolled (2.9% enrollment yield) and 166 completed the study (82% retention rate). …”
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Integrating digital and narrative medicine in modern healthcare: a systematic review by Efthymia Efthymiou

“…The increasing integration of digital technologies in healthcare, such as electronic health records, telemedicine, and diagnostic algorithms, improved efficiency but raised concerns about the depersonalization of care. …”
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Machine learning-driven prediction model for cuproptosis-related genes in spinal cord injury: construction and experimental validation by Yimin Zhou, Xin Li, Zixiu Wang, Liqi Ng, Rong He, Chaozong Liu, Gang Liu, Xiao Fan, Xiaohong Mu, Yu Zhou, Yu Zhou

“…Future research requires more in vitro and in vivo experiments to deeply explore regulatory mechanisms and develop intervention methods.…”
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Investigating the Complexity of Multidimensional Symptom Experiences in Patients With Cancer: Systematic Review of the Network Analysis Approach by Vincent Richard, Allison Gilbert, Emanuela Pizzolla, Giovanni Briganti

“…Two reviewers independently screened the articles and resolved inclusion disagreements through consensus. …”
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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

“…The objective of the current study was to identify if a functional lncRNA-based gene signature exists that regulates non-apoptotic RCD. We systematically screened immune-related lncRNAs associated with ferroptosis, necroptosis, and pyroptosis using the Pearson correlation algorithm (|Pearson R|> 0.4, P < 0.01) on 88 osteosarcoma patients and 122 normal controls that were selected from the TARGET and GETx databases. …”
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Melanoma risk prediction models by Nikolić Jelena, Lončar-Turukalo Tatjana, Sladojević Srđan, Marinković Marija, Janjić Zlata

“…A continuous melanoma database growth would provide for further adjustments and enhancements in model accuracy as well as offering a possibility for successful application of more advanced data mining algorithms.…”
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Combining Near-Infrared Spectroscopy and Chemometrics for Rapid Recognition of an Hg-Contaminated Plant by Bang-Cheng Tang, Hai-Yan Fu, Qiao-Bo Yin, Zeng-Yan Zhou, Wei Shi, Lu Xu, Yuan-Bin She

“…The NIRS measurements of impacted sample powders were collected in the mode of reflectance. The DUPLEX algorithm was utilized to split the NIRS data into representative training and test sets. …”
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A predictive model of cognitive impairment in Parkinson's disease based on multivariate logistic regression by BA Mengru, YIN Xiaohong, LI Shaoyuan

“…First, the least absolute shrinkage and selection operator (LASSO) algorithm was applied to analyze the risk factors that may affect the cognitive ability of patients, and the clinical variables with high correlation were screened out. …”
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Novel exosome-associated LncRNA model predicts colorectal cancer prognosis and drug response by Chi Zhou, Qian Qiu, Xinyu Liu, Tiantian Zhang, Leilei Liang, Yihang Yuan, Yufo Chen, Weijie Sun

“…More importantly, we conducted an in-depth study on MIR4713HG, which may become an important therapeutic target in CRC.…”
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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…The effects and main limitations of AI diagnosis were summarized through comprehensive analysis of research design, algorithmic methods, and experimental results from relevant literature. …”
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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study by Juan Xie, Run-wei Ma, Yu-jing Feng, Yuan Qiao, Hong-yan Zhu, Xing-ping Tao, Wen-juan Chen, Cong-yun Liu, Tan Li, Kai Liu, Li-ming Cheng

“…Therefore, this study aims to further optimize and expand the risk assessment tool to more efficiently identify high-risk individuals and compensate for the shortcomings of existing diagnostic methods. …”
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Machine learning in dentistry and oral surgery: charting the course with bibliometric insights by Shuangwei Liu, Yuquan Hao, Shijie Zhu, Liyao Wan, Zhe Yi, Zhichang Zhang

“…Conclusion ML has made remarkable progress in dentistry and oral surgery. …”
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Toxoplasmosis seroprevalence in rheumatoid arthritis patients: A systematic review and meta-analysis. by Zahra Hosseininejad, Mehdi Sharif, Shahabeddin Sarvi, Afsaneh Amouei, Seyed Abdollah Hosseini, Tooran Nayeri Chegeni, Davood Anvari, Reza Saberi, Shaban Gohardehi, Azadeh Mizani, Mitra Sadeghi, Ahmad Daryani

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The microRNA expression signature of CD4+ T cells in the transition of brucellosis into chronicity. by Ferah Budak, Salih Haldun Bal, Gulcin Tezcan, Emin Halis Akalın, Abdullah Yılmaz, Pınar Hız, Haluk Barbaros Oral

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Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review by Jie Li, Manli Zhu, Li Yan

“…Background With the development of artificial intelligence, the application of machine learning to develop predictive models for sepsis-associated acute kidney injury has made potential breakthroughs in early identification, grading, diagnosis, and prognosis determination.Methods Here, we conducted a systematic search of the PubMed, Cochrane Library, Embase (Ovid), Web of Science, and Scopus databases on April 28, 2023, and screened relevant literature. …”
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