Search Results - "algorithm"

Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth develop... by Jiahe Liu, Lang Chen, Yuxin Chen, Jingsong Luo, Kexin Yu, Linlin Fan, Chan Yong, Huiyu He, Simei Liao, Zongyuan Ge, Lihua Jiang, Lihua Jiang

“…Our study aimed to examine the risk factors associated with IA among Chinese children and adolescents and leverage explainable machine learning (ML) algorithms to predict IA status at the time of assessment, based on Young’s Internet Addiction Test.MethodsThe longitudinal data consisting of 8,824 schoolchildren from the Chengdu Positive Child Development (CPCD) survey were analyzed, where 33.3% of participants were identified with IA (Age: 10.97 ± 2.31, Male: 51.73%). …”
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Single-Cell Transcriptomics Unveils the Mechanistic Role of FOSL1 in Cutaneous Wound Healing by Jingbi Meng, Ge Zheng, Yinli Luo, Ling Ge, Zhiqing Liu, Wenhua Huang, Meitong Jin, Yanli Kong, Shanhua Xu, Zhehu Jin, Longquan Pi

“…Subsequently, we constructed Protein–Protein Interaction (PPI) networks via the STRING database. Machine learning algorithms were instrumental in identifying pivotal genes, a finding corroborated through animal modeling and Western blot analysis of tissue samples. …”
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Results of a non-interventional multicenter observational study on the diagnosis and treatment of patients with axial psoriatic arthritis in rea-world clinical practice in the Russ... by T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, Yu. L. Korsakova, E. A. Vasilenko, I.-D. Yu. Ilyevsky, L. V. Ivanova, E. Yu. Akulinushkina, P. А. Shesternya, O. V. Matveychuk, Yu. Yu. Grabovetskaya, A. A. Barakat, M. A. Korolev, E. V. Zonova, O. A. Georginova, I. V. Kolotilina, I. M. Marusenko, I. B. Vinogradova, O. B. Nesmeyanova, N. E. Grigoriadi, A. V. Petrov, D. G. Krechikova, T. V. Kropotina, S. P. Yakupova, V. I. Mazurov

“…Switching therapy to bDMARDs led to a significant reduction in disease activity.In order to improve the quality of medical care, the Russian clinical guidelines for the treatment of patients with PsA and the algorithms for the diagnosis of axial involvement need to be comprehensively implemented.…”
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Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Conservative treatment with pentoxifylline, gabapentin, and physical therapy improved his symptoms. (2) Methods: The original treatment plan was retrospectively analyzed using Monte Carlo dose algorithms and LET-dependent RBE models from McMahon and McNamara. …”
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Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study by Chengkun Sun, Erin Mobley, Michael Quillen, Max Parker, Meghan Daly, Rui Wang, Isabela Visintin, Ziad Awad, Jennifer Fishe, Alexander Parker, Thomas George, Jiang Bian, Jie Xu

“…Given the distinct pathology of colon cancer (CC) and rectal cancer (RC), we created separate prediction models for each cancer type with various ML algorithms. We assessed multiple prediction time windows (ie, 0, 1, 3, and 5 y) and ensured robustness through propensity score matching to account for confounding variables including sex, race, ethnicity, and birth year. …”
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Cancer incidence in young adults aged 20 to 44 years old in the Siberian Federal District by L. D. Zhuikova, E. L. Choynzonov, A. D. Kaprin, A. O. Shakhzadova, O. A. Ananina, G. A. Kononova, L. V. Pikalova, M. Yu. Grishchenko, E. V. Denisov

“…The results of the study update the development of new organizational and clinical algorithms for medical observation of young men and women for the purpose of prevention or early diagnosis of tumor pathology, including for creating the feasibility of performing organpreserving treatment while preserving the reproductive potential of young patients.…”
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Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer by Ruoya Wang, Shouliang Cai, Qing Gao, Yidong Chen, Xue Han, Fangjian Shang, Chunyan Liang, Guolian Zhu, Bo Chen

“…Additionally, we analyzed the immune microenvironment and enriched pathways across different subtypes using multiple algorithms. Finally, the “oncoPredict” R package was used to assess potential drug sensitivities in high-risk and low-risk groups.ResultsSeventeen polyamine metabolism genes were identified. …”
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On the construction of a large-scale database of AI-assisted annotating lung ventilation-perfusion scintigraphy for pulmonary embolism (VQ4PEDB) by Amir Jabbarpour, Eric Moulton, Eric Moulton, Sanaz Kaviani, Sanaz Kaviani, Siraj Ghassel, Wanzhen Zeng, Wanzhen Zeng, Ramin Akbarian, Ramin Akbarian, Anne Couture, Aubert Roy, Richard Liu, Yousif A. Lucinian, Nuha Hejji, Nuha Hejji, Sukainah AlSulaiman, Sukainah AlSulaiman, Farnaz Shirazi, Farnaz Shirazi, Eugene Leung, Eugene Leung, Sierra Bonsall, Samir Arfin, Bruce G. Gray, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…Quality assurance involved manual inspections and algorithmic validation.ResultsA query of The Ottawa Hospital's data warehouse followed by initial data screening yielded 2,137 V/Q studies with 2,238 successfully retrieved as DICOM studies. …”
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Screening of potential markers for vitiligo based on bioinformatics and LASSO regression and prediction of Chinese medicine by Wei Liang, Minni Huang, Yue Sun, Shuyu Guan

“…Nineteen core genes were screened out from the five algorithms of Cytohubba, and LASSO regression analysis further determined four key genes (IL7R, GZMH, CD3G, and UBD). …”
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Review of the Epidemiological Situation on Ixodic Tick-Borne Borrelioses in the Russian Federation in 2013–2022 and Forecast for 2023 by S. A. Rudakova, O. E. Teslova, N. E. Mutalinova, N. A. Pen’evskaya, A. I. Blokh, N. V. Rudakov, D. A. Savel’ev, Yu. F. Kuz’menko, D. V. Trankvilevsky

“…There is an obvious need to develop algorithms for molecular-genetic monitoring of pathogens circulating in natural foci, and to focus attention onto the problems of diagnosis and prophylaxis of tick-borne transmissible infections.…”
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Chemoreactome prediction of anti-inflammatory, analgesic, ulcerogenic effects of the candidate molecule N-allylimidazole-zinc in comparison with zinc derivatives of nonsteroidal an... by P. A. Galenko-Yaroshevsky, A. V. Sergeeva, I. Yu. Torshin, A. N. Gromov, I. A. Reyer, O. A. Gromova, B. A. Trofimov, L. N. Parshina, R. A. Murashko, A. V. Zadorozhniy, A. V. Zelenskaya, N. S. Sergeev, Yu. V. Tovkach, O. N. Gulevskaya, I. V. Sholl

“…The pharmacological capabilities of molecules within chemoreactome methodology are assessed by comparing the chemical structure of racetam molecules with the structures of molecules for which the molecular pharmacological properties have been studied using artificial intelligence learning algorithms based on big data information presented in PubChem, HMDB, STRING, PharmGKB databases. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol by Martin Eklund, Brett Delahunt, Lars Egevad, Hemamali Samaratunga, Mattias Rantalainen, Marcello Gambacorta, Einar Gudlaugsson, Bodil Ginnerup Pedersen, Xiaoyi Ji, Karina Dalsgaard Sørensen, Kelvin Szolnoky, Nita Mulliqi, Anders Blilie, Henrik Olsson, Matteo Titus, Geraldine Martinez Gonzalez, Sol Erika Boman, Masi Valkonen, Svein Reidar Kjosavik, José Asenjo, Paolo Libretti, Marcin Braun, Radzislaw Kordek, Roman Łowicki, Kristina Hotakainen, Päivi Väre, Benedicte Parm Ulhøi, Pekka Ruusuvuori, Toyonori Tsuzuki, Emilius Adrianus Maria Janssen, Kimmo Kartasalo

“…Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images show promise in improving the accuracy and efficiency of histopathological assessments. …”
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Efficacy and safety of ruxolitinib combined with steroids for first-line treatment of acute graft-versus-host disease after hematopoietic stem cell transplantation: a single-center... by Yan Yang, Yuan Huo, Dong Zhou, Zhijie Kang, Yanan Huang, Ying Wang, Guangjun Fan, Liyuan Ma, Jinsong Yan, Jinsong Yan, Jinsong Yan

“…Steroids are the standard first-line treatment for acute GVHD (aGVHD); however, standardized treatment algorithms for patients who do not respond to steroid therapy are lacking. …”
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Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis by Peize Yu, Peize Yu, Qikai Zhong, Qikai Zhong, Xinlei Wang, Xinlei Wang, Yifang Liu, Qiang Liu, Qiang Liu, Yuqiang Zhang, Jiawei Lu, Yang Dong, Cong-hui Han, Cong-hui Han

“…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. …”
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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of <i>T. japonicus</i> density. …”
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea by Lifeng Li, Qimeng Shi, Bowen Fang, Yuting Liu, Xiang Liu, Yongqiang Shu, Yingke Deng, Yumeng Liu, Haijun Li, Junjie Zhou, Dechang Peng

“…Additionally, we employed three machine learning algorithms—support vector machine (SVM), random forest (RF), and logistic regression (LR)—to distinguish patients with OSA from HC based on FC features. …”
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Cerebral oxygen saturation in relation to end-tidal CO2 in cardiopulmonary resuscitation – Separate views of brain and body? by Andrea Kornfehl, Roman Brock, Christoph Veigl, Veronique Firich, Mathias Gatterbauer, Michael Girsa, Daniel Grassmann, Andreas Zajicek, Alexander Spiel, Christoph Testori, Michael Holzer, Mario Krammel, Thomas Uray, Sebastian Schnaubelt

“…Further research should examine the potential of using rSO2 alongside etCO2 in CPR algorithms.…”
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Machine learning aids in the discovery of efficient corrosion inhibitor molecules by Haiyan GONG, Lingwei MA, Dawei ZHANG

“…Continuously optimizing ML algorithms and combining them with experimental validation should contribute to the efficient and high-precision discovery of corrosion inhibitor molecules in the future, leading to breakthroughs in materials science and industrial applications.…”
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