Search Results - "algorithm"

Exploring the Potential Regulatory Mechanisms of Mitophagy in Ischemic Cardiomyopathy by Li Z, Kong J, Xi S, Jin Z, Yang F, Zhu Z, Liu L

“…Then, biomarkers were identified through machine learning algorithms and Receiver Operating Characteristic curve (ROC) analysis. …”
Get full text

Carbapenemases Produced by Multidrug-Resistant Strains of <i>Klebsiella Pneumoniae</i> Isolated from Intensive Care Patients by T. V. Chernenkaya, L. A. Borisova, T. Yu. Vorobieva, M. A. Godkov, A. K. Shabanov

“…In 11.3% of carbapenem-resistant strains, the production of KPC, OXA-48, NDM, VIM and IMP genes was not detected. When developing algorithms for antibacterial therapy, it is necessary to take into account that from 25.7% to 60.6% of K. pneumoniae strains in different intensive care units are the producers of metallobetalactamases.…”
Get full text

Research on the spatial layout of the elderly care industry based on explainable machine learning: A case study of Hangzhou(基于可解释性机器学习的养老产业空间布局研究)... by 曾笑奇(ZENG Xiaoqi), 赵秋皓(ZHAO Qiuhao), 冯友建(FENG Youjian)

“…The results indicate that∶ (1) SHAP effectively interprets the results of the machine learning algorithms; (2) Most factors, such as population size and government institutions, positively impact the layout of elderly care facilities, whereas other factors, such as financial service facilities, negatively impact their layout; (3) Future construction of elderly care facilities in Hangzhou should prioritize the central districts of Shangcheng and Gongshu as well as their surrounding areas, while development in Fuyang and Lin'an districts could be moderated. …”
Get full text

The implementation of the situational control concept of information security in automated training systems by A. M. Chernih, S. V. Fedoseev

“…Developed method of situational control of information security in automated learning systems, involves the participation of the operator in the development and decision-making (dialogue procedures statement of objectives situational control, the formation of the base of alternative sets of control actions, etc.).Another important feature of this technique is the necessity of using previously developed models (models of decision-making situation, a model of coordination and planning of operation of a subsystem of the control and protection of information, models of information processing about the status of the subsystem analysis models and evaluation of results) and the database obtained on the basis of operating experience of information protection systems in the automated learning systems.The implementation of the concept of situational control of information security ensures the timely adaptation of the algorithms and parameters of the information security system to changes in the external environment and the nature of tasks within the education systems and on this basis allows to improve the characteristics of the information protection system in the automated learning systems.…”
Get full text

Energy-Aware and Reliability-Based Localization-Free Cooperative Acoustic Wireless Sensor Networks by Junaid Qadir, Ubaid Ullah, Beatriz Sainz-De-Abajo, Begona Garcia Zapirain, Goncalo Marques, Isabel de la Torre Diez

“…The MATLAB simulations results validated the performance of the proposed algorithms. The EPACA protocol consumed 29.01&#x0025; and the CoEPACA protocol 19.04&#x0025; less energy than the counterpart scheme. …”
Get full text

Genetic variants of the DLK1, KISS1R, MKRN3 genes in girls with precocious puberty by E. A. Sazhenova, O. Yu. Vasilyeva, E. A. Fonova, M. B. Kankanam Pathiranage, A. Yu. Sambyalova, E. E. Khramova, L. V. Rychkova, S. A. Vasilyev, I. N. Lebedev

“…The pathogenicity of identified genetic variants and the functional significance of the protein synthesized by them were analyzed according to recommendations for interpretation of NGS analysis results using online algorithms for pathogenicity prediction (Variant Effect Predictor, Franklin, Varsome, and PolyPhen2). …”
Get full text

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recog... by Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

“…The collected data will then be used to train models with a neural network, which will then be validated against other models and compared with other algorithms. Demographic, psychological, digital biomarkers, and craving profiles will be created, correlations will be analyzed, and they will be compared with controls to generate a digital phenotype of SUD. …”
Get full text

Integrated multi-omics analysis and machine learning identify G protein-coupled receptor-related signatures for diagnosis and clinical benefits in soft tissue sarcoma by Duo Wang, Duo Wang, Duo Wang, Jihao Tu, Jihao Tu, Jianfeng Liu, Jianfeng Liu, Yuting Piao, Yuting Piao, Yiming Zhao, Yiming Zhao, Ying Xiong, Ying Xiong, Jianing Wang, Jianing Wang, Xiaotian Zheng, Xiaotian Zheng, Bin Liu, Bin Liu

“…We developed a novel machine learning framework that incorporated 12 machine learning algorithms and their 127 combinations to construct a consensus GPRS to screen biomarkers with diagnostic significance and clinical translation, which was assessed by the internal and external validation datasets. …”
Get full text

Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…Studies with insufficient data regarding the output variable used to assess the reliability of the ML model, those applying deterministic algorithms, unrelated topics, protocol studies, and other systematic reviews were excluded from the final synthesis. …”
Get full text

Predicting habitat suitability for conservation of IUCN- red listed medicinal species Chloroxylon swietenia DC., in Tamil Nadu, India using ensemble modeling by Rajendran Silambarasan, Kasthuri Nair A, Maniyan Gomathi, Hareendran Nair J, Nishanth Kumar S, Shan Sasidharan

“…We incorporated 19 bioclimatic variables, four soil-related variables (bulk density), and five land use/land cover variables (tree cover, cultivated land, water, and built-up areas) to model the species' habitat suitability across four Shared Socio-economic Pathways (SSPs) for the periods 2021–2040, 2041–2060, 2061–2080, and 2081–2100, using two different climate projections: BCC_CSM2-MR and EC-Earth3-Veg. Among the algorithms tested, the Random Forest model exhibited the highest performance. …”
Get full text

Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. Ten dental implants were retrospectively included in this IRB-approved study. …”
Get full text

Oxidative balance score predicts chronic kidney disease risk in overweight adults: a NHANES-based machine learning study by Leying Zhao, Leying Zhao, Cong Zhao, Cong Zhao, Yuchen Fu, Yuchen Fu, Xiaochang Wu, Xiaochang Wu, Xuezhe Wang, Xuezhe Wang, Yaoxian Wang, Yaoxian Wang, Yaoxian Wang, Huijuan Zheng

“…Additionally, 14 machine learning algorithms were trained and validated using SMOTE-balanced data and five-fold cross-validation. …”
Get full text

Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.ResultsLow STAT3 expression was significantly associated with poorer OS (hazard ratio [HR] = 1.927, p &lt; 0.001). …”
Get full text

Non-Celiac Villous Atrophy—A Problem Still Underestimated by Katarzyna Napiórkowska-Baran, Paweł Treichel, Adam Wawrzeńczyk, Ewa Alska, Robert Zacniewski, Maciej Szota, Justyna Przybyszewska, Amanda Zoń, Zbigniew Bartuzi

“…These findings highlight significant diagnostic challenges and underscore the need to adapt diagnostic algorithms that combine clinical history, serologic evaluations, and histopathologic analysis. …”
Get full text

An improved hybrid approach involving deep learning for urban greening tree species classification with Pléiades Neo 4 imagery—A case study from Nanjing, Eastern China by Min Sun, Stephane G.P. Debulois, Zhengnan Zhang, Xiaolei Cui, Zhili Chen, Mingshi Li

“…Future work will integrate multi-source data, multi-seasonal observations, and adaptive algorithms to further enhance classification performance and improve model robustness across diverse urban environments.…”
Get full text

Machine learning-based cotton yield forecasting under climate change for precision agriculture by Muhammad Umair Shahzad, Sana Tahir, Javed Rashid, Osama A. Khashan, Rashid Ahmad, Sheikh Mansoor, Anwar Ghani

“…This study employs a diverse range of machine learning (ML) methods, including multiple regression, k-nearest neighbors (KNN), boosted tree algorithms, and various types of artificial neural networks (ANNs), to investigate the intricate relationship between climate factors and cotton yields. …”
Get full text

High-density lipoproteins, Part 1. Epidemiology, antiatherogenic effects, and therapies designed to increase their serum levels by Beata Franczyk, Ewelina Młynarska, Magdalena Rysz-Górzyńska, Anna Gluba-Sagr, Jacek Rysz, Sohum Sheth, Stanislaw Surma, Maciej Banach, Peter P. Toth

“…A polymolecular assembly as complex as mature HDL is not a simple task to study. Risk algorithms need to reassess the validity of attributing cardioprotection from high HDL-C as this may lead to underestimation of true risk.…”
Get full text

Harnessing multi-omics and artificial intelligence: revolutionizing prognosis and treatment in hepatocellular carcinoma by Zhen Wang, Zhen Wang, Zhen Wang, Gangchen Zhou, Gangchen Zhou, Rongchuan Cao, Rongchuan Cao, Guolin Zhang, Guolin Zhang, Yongxu Zhang, Yongxu Zhang, Mingyue Xiao, Longbi Liu, Longbi Liu, Xuesong Zhang

“…To identify distinct molecular subtypes, a multi-omics data integration approach was employed, utilizing 10 distinct clustering algorithms. Survival analysis, immune infiltration profiling and drug sensitivity predictions were then used to evaluate the prognostic significance and therapeutic responses of these subtypes. …”
Get full text

Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…Among eight machine learning algorithms evaluated, the optimal model was selected to construct a predictive framework for immunotherapy response.ResultsMicrobial α-diversity was significantly elevated in responders compared to non-responders, with antibiotic administration further amplifying this difference—most notably at the species level. …”
Get full text

Advanced classification of optical water types and ensemble learning models for Chl-a inversion in Dongting and Poyang lakes using Sentinel-2 remote sensing: assessing the impact o... by Kai Xiong, Bin Deng, Jiang Liu, Zhixin Guan, Weizhi Lu, Changbo Jiang, Wei Luo, Han Rao, Longbin Yin, Kang Yang

“…This study proposes an integrated framework combining optical water type (OWTs) classification and ensemble learning algorithms to enhance the re- mote sensing retrieval accuracy of Chl-a in Dongting Lake and Poyang Lake during 2020–2023, particularly during the extreme drought event of 2022. …”
Get full text