Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop by Rano Agustino

“…By using CART classification, NBC (Naive Bayes Classifier) algorithm, SVM (Support Vector Machine), LR (Logis Text Regression) and LDA (Linear Discriminant Analysis) which will be compared which accuracy is the best for predicting the absence or absence of the audience. …”
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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…As machine learning algorithms become increasingly accessible, a growing number of organizations and researchers are using these technologies to automate the process of exoplanet detection. …”
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Application of quasi-oppositional driving training-based optimization for a feasible optimal power flow solution of renewable power systems with a unified power flow controller by Tushnik Sarkar, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Ghanshyam G. Tejani, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Obtaining minimum total cost comes under the single-objective function. Simultaneous reduction in the overall cost and emission, concurrent reduction in overall cost and voltage deviation (VD), and simultaneous reduction in overall cost and voltage stability index come under multi-objective cases. …”
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Machine learning and multi-omics analysis reveal key regulators of proneural–mesenchymal transition in glioblastoma by Can Xu, Jin Yang, Huan Xiong, Xiaoteng Cui, Yuhao Zhang, Mingjun Gao, Lei He, Qiuyue Fang, Changxi Han, Wei Liu, Yangyang Wang, Jin Zhang, Ying Yuan, Zhaomu Zeng, Ruxiang Xu

“…The TIDE algorithm was used to examine immunotherapy scores. …”
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Identification of neutrophil extracellular trap-related biomarkers in ulcerative colitis based on bioinformatics and machine learning by Jiao Li, Yupei Liu, Zhiyi Sun, Suqi Zeng, Caisong Zheng

“…Gevokizumab, canakinumab and carboxylated glucosamine were predicted as potential therapeutic drugs for UC.ConclusionBy combining three machine learning algorithms and bioinformatics, this research identified three hub genes that could serve as novel targets for the diagnosis and therapy of UC, which may provide valuable insights into the mechanism of NETs in UC and potential related therapies.…”
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Identification of Plasma Exosomes hsa_circ_0001360 and hsa_circ_0000038 as Key Biomarkers of Coronary Heart Disease by Wan Zhang, Jiasen Cui, Li Li, Ting Zhu, Zhenyu Guo

“…Multiple machine learning algorithms have been used to explore potential biomarkers, followed by verification in patients with CHD using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). …”
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Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network by Xingyu Duan, Xiaojun Ma, Mengqi Zhu, Linan Wang, Dingqi You, Lili Deng, Ningkui Niu

“…Results Following the segmentation of bare back images and the application of computer vision algorithms, the Dual AttentionUNet model achieved an accuracy, precision, and recall rate of over 90% in predicting severe scoliosis. …”
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Integrating Metabolomics and Machine Learning to Analyze Chemical Markers and Ecological Regulatory Mechanisms of Geographical Differentiation in <i>Thesium chinense</i> Turcz by Cong Wang, Ke Che, Guanglei Zhang, Hao Yu, Junsong Wang

“…Random forest and LASSO regression algorithms determined core markers for each production area: Anhui (4 markers), Henan (6 markers), and Shanxi (3 markers). …”
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Integration of bulk RNA-seq and scRNA-seq reveals transcriptomic signatures associated with deep vein thrombosis by Bao-ze Pan, Ming-jun Jiang, Li-ming Deng, Jie Chen, Xian-peng Dai, Zi-xuan Wu, Zhi-he Deng, Dong-yang Luo, Yang-yi-jing Wang, Dan Ning, Guo-zuo Xiong, Guo-shan Bi

“…Topology analysis was performed using seven protein-protein interaction (PPI) network algorithms. The combination of weighted correlation network analysis (WGCNA) and clinical prediction models was employed to validate hub DEGs. …”
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Oil Commodity Movement Estimation: Analysis with Gaussian Process and Data Science by Mulue Gebreslasie, Indranil SenGupta

“…In this study, Gaussian process (GP) regression is used to normalize observed commodity data and produce predictions at densely interpolated time intervals. …”
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Multiplex immunophenotyping of human acute myeloid leukemia patients revealed single -cell heterogeneity with special attention on therapy sensitive and therapy resistant subpopula... by Nikolett Gémes, Benedek Rónaszéki, Szabolcs Modok, Zita Borbényi, Imre Földesi, Éva Trucza, Blanka Godza, Zsuzsanna László, Balázs Csernus, László Krenács, Enikő Bagdi, Enikő Szabó, László G. Puskás, László G. Puskás, Valeria Bertagnolo, Gábor J. Szebeni, Gábor J. Szebeni, Gábor J. Szebeni

“…Unsupervised clustering algorithms such as Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) and Flow cytometry data that builds Self-Organizing Maps (FlowSOM) were used to reveal the LAIP. …”
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An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
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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. …”
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An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto, Geraldo Pereira Rocha Filho

“…The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. …”
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Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…The experimental results indicate that: 1) The improved YOLOv5n model exhibits a 56.8% reduction in parameters, a 56.1% decrease in giga floating point operations per second (GFLOPs), a 51.4% reduction in model size, and a 37.0% reduction in Embedded Device Inference Time compared to the YOLOv5n model. …”
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High-Throughput cDNA Screening Utilizing a Low Order Neural Network Filter by Guyang Matthew Huang, James Farkas, Leroy Hood

“…Evaluation of the detections with two other dissimilar computer prediction algorithms yielded strong transmembrane predictions for 15 of the detections, while 8 of the detections resulted in a definitive negative result. …”
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Simultaneous replacement of the aortic valve and hip joint in a patient with critical aortic stenosis and femoral neck fracture by S. V. Petrov, A. S. Peleshok, V. L. Ignatenko, O. M. Mutalibov, V. A. Krivopalov, G. G. Khubulava, N. G. Pilyugov

“…Developing the treatment algorithm for a combination of two or more diseases in this category of patients is the main task. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…A detailed comparative analysis was conducted, examining key parameters such as learning rate, optimization algorithms, and the number of training epochs to determine the most effective approach. …”
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EFFICACY OF CARDIOVERTER-DEFIBRILLATORS IN PREVENTION OF SUDDEN DEATH AND OVERALL MORTALITY DECREASE IN PATIENTS WITH THE SYNDROME OF DILATION CARDIOMYOPATHY: DIFFERENTIAL APPROA... by O. V. Blagova, A. V. Nedostup, E. V. Zaklyazminskaya

“…Main predictors of the shocks were genetic origin of DCMP (isolated or with myocarditis, 25/75%, comparing with 20/33% in patients with no shocks, p&lt;0,01, HR 1,58, OR 10,93, sensitivity 94,1%, negative predictive value 99,2%), and sustained (HR 18,0, sensitivity 98,1%) and non-sustained ventricular tachycardia (HR 1,43, sensitivity and negative predictive value 100%), decrease of QRS voltage and absence of the signs of LV hypertrophy on ECG (negative predictive value 92,8% and 95,6%).Conclusion. …”
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