Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas by Yue Hu, Xin Cao, Hongyi Chen, Daoying Geng, Kun Lv

“…The logical regression, random forest, support vector machine (SVM) and adaptive boosting algorithms were used to establish models. The model performance was evaluated using area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. …”
Get full text

Integrating bioinformatics and machine learning to elucidate the role of protein glycosylation-related genes in the pathogenesis of diabetic kidney disease. by Ziyang Liu, Zengyuan Qin, Wenxin Bai, Shasha Wang, Chunling Huang, Na Li, Lei Yan, Yue Gu, Fengmin Shao

“…Functional enrichment, immune cell infiltration analysis, and machine learning algorithms (including feature selection for hub genes) were employed. qPCR validation was performed on clinical DKD and normal kidney tissues, and ROC curves were generated to assess diagnostic potential.…”
Get full text

Face Anti-spoofing Detection Based on Novel Encoder Convolutional Neural Network and Texture’s Grayscale Structural Information by Marwa Radad, Amira E. Enab, Salah S. Elagooz, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

“…We contrast our proposed method with alternative algorithms and verify its performance using three publicly available datasets, showcasing its superiority.…”
Get full text

EVOLUTION OF THE MARKETING PARADIGM: A NEW VISION by G. V. Astratova, O. A. Rushchitskaya

“…., theory of stages of marketing evolution); 3) values in the context of the marketing paradigms are considered by the authors through emphasis on three research objects: a) goods (service) - creation of new goods and/or formation of a set of qualities inherent in the goods (service), perceived by the consumer as a combination of rational and emotional values of the product; b) customer - development of "value proposition for the consumer"; c) seller/manufacturer - basing on the concept of "value chain" that builds strategic management of the company; 4) conventional samples of the marketing paradigm include standards, or algorithms, models and methods of solving specific problems of marketing research (for example, a diagram of the stages of the marketing research process and industrial standards of their conduct). …”
Get full text

SURGICAL TREATMENT OF MULTIFOCAL ATHEROSCLEROSIS: CORONARY AND BRACHIOCEPHALIC PATHOLOGY AND PREDICTORS OF EARLY ADVERSE EVENTS DEVELOPMENT by R. S. Tarasov, A. N. Kazantsev, S. V. Ivanov, N. N. Burkov, A. I. Anufriev, L S. Barbarash

“…The results can be applied in algorithms development for selection of surgical tactics in multifocal atherosclerosis patients.…”
Get full text

Identification of factors associated with acute malnutrition in children under 5 years and forecasting future prevalence: assessing the potential of statistical and machine learnin... by Christopher Coffey, Meike Reusken, Frans Cruijssen, Bertrand Melenberg, Cascha van Wanrooij

“…We then applied tree-based machine learning algorithms to a dataset comprising the GAM prevalence estimates and associated factors to try to forecast the trajectory and fluctuations in GAM prevalence 6 months into the future.Results We found factors statistically associated with GAM prevalence relating to rainfall, land vegetation quality, food security status, crop production and demographics. …”
Get full text

Prevention of falls in hospitalized patients—evaluation of the effectiveness of a monitoring system (Verso Vision) developed with artificial intelligence by Corrado Gervasi, Erik Perego, Francesca Galli, Valter Torri, Massimo Castoldi, Emilio Bombardieri

“…The Verso Vision System (VS) is an artificial intelligence-based system for accidental fall prevention and management, which uses computer vision algorithms to monitor environments and people in real time.MethodsThe efficacy of VS monitoring in terms of reduction of accidentals falls was retrospectively evaluated in a group of 362 hospitalized patients at Humanitas Gavazzeni Hospital.ResultsOf the 362 patients included in the analysis, 580 statistical units, 228 monitored with VS and 355 without VS were obtained splitting the observation of each patient based on the presence of VS monitoring and the Stratify score. …”
Get full text

Instances for the problem of pre-positioning emergency supplies by Renata Turkeš, Kenneth Sörensen

“…In addition, the authors developed a tool to algorithmically generate arbitrarily many diverse random instances of any size. …”
Get full text

A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

“…By applying the proposed methods to a resting-state fMRI dataset including 179 subjects, both algorithms successfully reveal significant group differences in functional network connectivity between healthy controls and schizophrenia patients. …”
Get full text

Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification by Nuan Cui, Yingjie Wu, Guojiang Xin, Jiaze Wu, Liqin Zhong, Hao Liang

“…Class Activation Mapping (CAM) algorithms generated heatmaps visualizing influential regions. …”
Get full text

Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…Methods A multidisciplinary design comprising machine learning algorithms mixed with a descriptive, cross-sectional, correlational design was implemented to enhance data analysis and decision-making. …”
Get full text

Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…Multi-feature-based maritime radar target detection algorithms often rely on statistical models to accurately characterize sea clutter variations. …”
Get full text

Evaluation of Machine Learning Models for Sentiment Analysis in the South Sumatra Governor Election Using Data Balancing Techniques by Febriyanti Panjaitan, Win Ce, Hery Oktafiandi, Ghanim Kanugrahan, Yudi Ramdhani, Vito Hafizh Cahaya Putra

“…This study compares five machine learning algorithms (SVM, Naïve Bayes, KNN, Decision Tree, and Random Forest) and examines the impact of data balancing on their performance. …”
Get full text

UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

“…Finally, we validate the effectiveness of the proposed heterogeneous hardware acceleration framework through experiments. For specific algorithms, our implementation achieves a state of the art acceleration effect compared to previous work. …”
Get full text

Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning by Max Anjos, Fred Meier

“…Here, we introduce a ML-based bottom-up framework to predict hourly CO2 emissions from vehicular traffic at fine spatial resolution (30 × 30 m). Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO2 emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. …”
Get full text

Implementation of a Universal Screening and Referral Program for University Students at Risk of Suicide: A Case Study and Recommendations by Penelope Hasking, Kealagh Robinson, Kate Tonta

“…Traditional risk assessment approaches are unreliable, prompting calls for psychosocial assessments with multivariable algorithms grounded in person-centred approaches. This paper outlines considerations in implementing one such program, identifying potential implementation barriers and offering recommendations for minimising them. …”
Get full text

Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

“…By using advanced techniques such as Word2Vec and FastText, we experimented with different hyperparameter configurations, such as vector size, window size, and training algorithms (CBOW and skip-gram), to analyze their impact on model quality. …”
Get full text

Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

“…Lately, several studies have delved into cancer classification by leveraging data mining techniques, machine learning algorithms, and statistical methods to thoroughly analyze high-dimensional datasets. …”
Get full text

Transcriptomic analysis and machine learning modeling identifies novel biomarkers and genetic characteristics of hypertrophic cardiomyopathy by Feng Zhang, Chunrui Li, Lulu Zhang

“…A predictive model for HCM was developed through systematic evaluation of 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on training datasets and external validation using an independent cohort (GSE180313).ResultsA total of 271 DEGs were identified, primarily enriched in multiple biological pathways. …”
Get full text

Calculation of Derivatives in the Lp Spaces where 1 ≤ p ≤ ∞ by Anatoly Nikolaevich Morozov

“….\) The constructions are algorithmic in nature and can be applied in numerical computer research of various differential models.…”
Get full text