Search Results - statistical algorithm

POLYPHARMACY IN MANAGMENT OF IN-PATIENTS WITH NOVEL CORONAVIRUS DISEASE (COVID-19) by V. I. Petrov, A. Yu. Ryazanova, N. S. Privaltseva, D. A. Nekrasov

“…Lack of drugs with proven effectiveness for treatment of COVID-19, worked-out treatment algorithms, a high mortality of patients in the hospitals led to polypragmasy, excessive prescribing of drugs in the hospitals. …”
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Prevalence and risk of bone fractures in patients with chronic pancreatitis: meta-analysis by D. N. Andreev, I. V. Maev, Yu. A. Kucheryavyy

“…Considering this association, it is advisable to include densitometry in the routine examination algorithms for patients with chronic pancreatitis, as well as to correct osteoporosis in this category of patients in time.…”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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A machine learning model for predicting lymph node positivity in ovarian cancer: development, validation, and clinical application by QingYong Guo, Jinji Wang, Ru Chen, LiPing Hu, Wenqiang You

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Standardized conversion model for retinal thickness measurements between spectral-domain and swept-source optical coherence tomography based on machine learning by Zhongping Tian, Yinning Guo, Xi Chen, Qifeng Zhou, Yuan Liu, Zhizhu Yi, Li Zhang, Li Zhang

“…Machine learning-derived conversion algorithms significantly improve cross-device comparability, offering a robust standardization framework for multicenter research and longitudinal data integration. …”
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Ethics, Animal Welfare, and Artificial Intelligence in Livestock: A Bibliometric Review by Taize Calvacante Santana, Cristiane Guiselini, Héliton Pandorfi, Ricardo Brauer Vigoderis, José Antônio Delfino Barbosa Filho, Rodrigo Gabriel Ferreira Soares, Maria de Fátima Araújo, Nicoly Farias Gomes, Leandro Dias de Lima, Paulo César da Silva Santos

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Determination of Colles fracture risk index by X-ray images with the computer vision application by Wisam A. Hussein, Hussain J. AlKhatteib, Jawad K. Abbas

“…The results showed statistically significant differences (p < 0.05), suggesting that image intensity is a potential predictor of fracture risk. …”
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Processing streams in a monitoring cloud cluster by Alexey N. Nazarov

“…Hadoop web-programming environment is the technological basis for the development of algorithmic and software solutions for the synthesis of monitoring clusters, including information security and information counteraction systems. …”
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Porcine Ovarian piRNA Dynamics: A Comparative Study During Follicular Atresia by Jinbi Zhang, Long Huang, Xinxin Qin, Wenjie Li, Xiaolong Cheng, Zengxiang Pan

“…In this study, we collected single antral follicles from the ovaries of 180-day-old commercial sows, classified them as healthy (HF) and atretic (AF) based on morphological and biochemical criteria, and sequenced the RNA samples using the Illumina Hiseq 3000 system (San Diego, CA, USA). piRNAs were identified using three algorithms, and the differential expression was compared and validated by qPCR. …”
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Identification of developmental and reproductive toxicity of biocides in consumer products using ToxCast bioassays data and machine learning models by Donghyeon Kim, Siyeol Ahn, Jinhee Choi

“…This analysis revealed 25 bioassays with statistically significant correlations to in vivo DART data. …”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. …”
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Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…The data obtained were analyzed using modern methods of biological statistics, including machine learning algorithms.Results. …”
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POSSIBILITIES OF CARIES PROGNOSIS IN CHILDREN OF SCHOOL-AGE ACCORDING TO DATA GAINED FROM THEM AND THEIR PARENTS QUESTIONNAIRE by L.F. Kaskova, T.B. Mandziuk, L.P. Ulasevych, L.D. Korovina, M.A. Sadovski

“…The quantitative indices obtained during the examination of patients were processed with standard methods of mathematical statistics. For the semi-quantitative and qualitative indices, the frequency tables were built. …”
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Population Cohort-Validated PM_2.5-Induced Gene Signatures: A Machine Learning Approach to Individual Exposure Prediction by Yu-Chung Wei, Wen-Chi Cheng, Pinpin Lin, Zhi-Yao Zhang, Chi-Hsien Chen, Chih-Da Wu, Yue Leon Guo, Hung-Jung Wang

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Sex differences in alcohol use patterns and related harms: A mixed-methods, cross-sectional study of men and women in northern Tanzania. by Madeline McNee, Niveditha Badrinarayanan, Eleanor Strand, Thiago Augusto Hernandes Rocha, Timothy Antipas Peter, Yvonne Sawe, Anna Tupetz, Diego Galdino França, Judith Boshe, Joao Ricardo Nickenig Vissoci, Monica H Swahn, Blandina Mmbaga, Catherine Staton

“…Differences in scores by sex were assessed using unpaired t-tests. K-means algorithms were run independently in both samples. Deductive thematic analysis was conducted on FGDs with community members, injury patients, and injury patient relatives. …”
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Biochemical disturbances in schizophrenia — a «window of opportunity» by T. V. Zhilyaeva, A. S. Piatoikina, E. D. Kasyanov, G. V. Rukavishnikov, I. V. Semennov, O. V. Kostina, A. S. Blagonravova, G. E. Mazo

“…Moreover, screening algorithms for the detection and personalized correction of controlled biomarkers have not been introduced into clinical practice yet.   …”
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Investigation of the Regularities of the Influence of Meteorological Factors on Avalanches in Eastern Kazakhstan by Marzhan Rakhymberdina, Natalya Denissova, Yerkebulan Bekishev, Gulzhan Daumova, Milan Konečný, Zhanna Assylkhanova, Azamat Kapasov

“…Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. …”
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SURGICAL TREATMENT OF SOLITARY ADRENAL METASTASIS FROM NON-SMALL CELL LUNG CANCER by A. G. Muradyan, A. A. Kostin, A. O. Tolkachev, N. V. Vorobyev

“…The presence of solitary adrenal metastasis from lung cancer provides survival benefit; however, currently, there are no exact treatment algorithms. Objectives of the study: to assess shortand long-term treatment outcomes in patients with adrenal metastases from NSCLC. …”
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Validation of Reference Genes for Accurate RT-qPCR Normalization in <i>Aeluropus littoralis</i> Under Drought, Cold, and ABA Treatments by Seyyed Hamidreza Hashemipetroudi, Ali Rezaei, Markus Kuhlmann

“…The validation analysis indicates a statistically significant difference (<i>p</i> value < 0.05) between normalization with the most and least stable CRGs. …”
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Development and Testing a New Online Dynamic Nomogram for Contrast-Induced Acute Kidney Injury in Elderly Patients with ST-Segment Elevation Myocardial Infarction by Jin J, Ding J, Zhang X, Wang L, Zhang X, Li W, Li S

“…Lasso regression selected predictors, and nine Machine Learning (ML) algorithms were evaluated via Receiver Operating Characteristic (ROC) analysis. …”
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