Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study by Zhihui Chen, Hongqing Zhu, Hongmin Shu, Jianbo Zhang, Kangchen Gu, Wenjun Yao

“…Using ITK-SNAP, two radiologists annotated tumor regions of interest (ROI) and extended surrounding areas by 1 mm, 3 mm, and 5 mm. The K-means clustering algorithm divided the tumor region into three sub-regions, and the Least Absolute Shrinkage and Selection Operator (LASSO) regression identified the most predictive features. …”
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Bi-modal ultrasound radiomics and habitat analysis enhanced the pre-operative prediction of axillary lymph node burden in patients with early-stage breast cancer by Jing Xu, Pan Qi, Xiaoyan Ou, Qiaoxin Zhong, Zhen-Wen Chen, Yin Wang, Aijiao Yi, Bin Wang

“…The feature extraction was manually delineated with ITK-SNAP software, while a K-means clustering algorithm was employed for the segmentation of sub-regions, with the number of clusters ranging from 2 to 10. …”
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Determination of the positioning accuracy of industrial manipulators using a digital photo/video camera by N. V. Norkina, F. A. Mevis

“…Possibilities of specification of positions of point sources by means of computer processing of the images received from the digital camera were investigated. …”
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Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)? by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Dimitrios A. Patikas, Nicholas A. Beckmann, Katharina S. Gather, Sebastian I. Wolf

“…Participants were divided into different response groups (poor, mild, and good gait quality) according to their pre- and post-treatment Gait Deviation Index (GDI), using the K-means-PSO clustering algorithm. The gait and EMG indices were compared between the responders using the nonparametric Mann–Whitney test. …”
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A Single Layer Neural Network Implemented by a <inline-formula><tex-math notation="LaTeX">$4\times 4$</tex-math></inline-formula> MZI-Based Optical Processor by Farhad Shokraneh, Simon Geoffroy-Gagnon, Mohammadreza Sanadgol Nezami, Odile Liboiron-Ladouceur

“…The required phase shifts to construct the linear transformation matrix by means of the optical processor are determined theoretically. …”
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Geoinformation monitoring of the educational risk in educational institutions of higher education by Aleksandr N. Kolesenkov, Dmitry S. Zhuravlyov

“…Assessment of the educational risk can be implemented through monitoring the quality of the implementation of the main professional educational programs of the institution.Monitoring of the educational risk in the implementation of the educational process in institutions of higher education means the collection, cataloging, pre-processing, analysis and visualization of the data, aimed at improving the efficiency and quality of providing educational services. …”
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«Pull» model of interaction of participants of a life cycle contract of vehicles by N. A. Amosov, E. Yu. Kuznetsova

“…A new challenge for manufacturers is the ability to manage the life cycle of vehicles. Control means monitoring and obtaining various data on the state and quality of the vehicle during the life cycle. …”
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The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets by Theresa Willem, Alessandro Wollek, Theodor Cheslerean-Boghiu, Martha Kenney, Alena Buyx

“…Our findings highlight the social constructedness of categorical data in publicly available datasets, meaning that the data in a category heavily depend on both how these categories are defined by the dataset creators and the sociomedico context in which the data are collected. …”
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Combined Effect of Maternal Vitamin D Deficiency and Gestational Diabetes Mellitus on Trajectories of Ultrasound-Measured Fetal Growth: A Birth Cohort Study in Beijing, China by Zheng Liu, Hui Liu, Xiangrong Xu, Shusheng Luo, Jue Liu, Chuyao Jin, Na Han, Hai-Jun Wang

“…Fetal growth was assessed by longitudinal ultrasound measurements of estimated fetal weight (EFW) and abdominal circumference (AC) from 28 gestational weeks to delivery, both of which were standardized as gestational-age-adjusted Z-score. A k-means algorithm was used to cluster the longitudinal measurements (trajectories) of fetal growth. …”
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The Mobile Complex of Chemical Control as the Basis of Technical Equipment of the Mobile Diagnostic Group of the 33 Central Scientific Research Test Institute of the Ministry of De... by V. A. Inozemtsev, A. K. Zhokhov, A. Yu. Boyko, A. S. Samorodov, A. V. Zhidyaev, A. A. Braginets

“…Subsequently, this methodological apparatus has been repeatedly expanded and refined based on the results of the complex's participation in ensuring the RCh security of various mass events. The algorithm of carrying out special chemical control by technical means of the MCCC complex is presented in the article. …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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Predicting Oncological and Functional Outcomes by Nephrectomy Type for T1 Renal Tumors Using Machine Learning Models by Dongrul Shin, Maisy Song, Jungyo Suh, Cheryn Song

“…Using machine learning algorithms, we aimed to develop a model to predict both outcomes simultaneously, according to each radical (RN) and partial nephrectomy (PN). …”
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Physics-informed machine learning to predict solvatochromic parameters of designer solvents with case studies in CO2 and lignin dissolution by Mood Mohan, Nikhitha Gugulothu, Sreelekha Guggilam, T. Rajitha Rajeshwar, Michelle K. Kidder, Jeremy C. Smith

“…To address this, the present study developed two different machine learning (ML) algorithms to predict Kamlet-Taft parameters for designer solvents using quantum chemically derived input features. …”
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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…Integrating machine learning algorithms leveraged by advanced data acquisition systems is emerging as a pivotal approach in predictive maintenance. …”
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Rice Yield Prediction Based on Simulation Zone Partitioning and Dual-Variable Hierarchical Assimilation by Jiaoyang He, Yanxi Zhao, Ping He, Minglei Yu, Yan Zhu, Weixing Cao, Xiaohu Zhang, Yongchao Tian

“…In this study, we first extracted high-resolution rice planting areas in Jiangsu Province (JP), then conducted simulation zone partitioning in JP based on the fuzzy c-means clustering algorithm (FCM) combined with soil data, meteorological indices, and EVI. …”
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Augmenting brain-computer interfaces with ART: An artifact removal transformer for reconstructing multichannel EEG signals by Chun-Hsiang Chuang, Kong-Yi Chang, Chih-Sheng Huang, Anne-Mei Bessas

“…Tackling this problem demands advanced algorithms, extensive noisy-clean training data, and thorough evaluation strategies. …”
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Developing advanced datadriven framework to predict the bearing capacity of piles on rock by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Fabián Danilo Reyes Silva, José Luis Allauca Palta, José Luis Llamuca Llamuca, Siva Avudaiappan

“…This research presents an advanced data-driven framework that integrates multiple machine learning algorithms to predict the bearing capacity of piles based on geotechnical and in-situ test parameters. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Patients scheduled by the intelligent model show higher mean propensities to attend appointments and to develop diseases, ensuring that medical resources are allocated efficiently to those in greatest need. …”
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Transcranial direct current stimulation and methylphenidate interact to increase cognitive persistence as a core component of metacontrol: Evidence from aperiodic activity analyses by Yang Gao, Anna Helin Koyun, Veit Roessner, Ann-Kathrin Stock, Moritz Mückschel, Lorenza Colzato, Bernhard Hommel, Christian Beste

“…Objective: We provide mechanistic insights into the neurobiological foundations of metacontrol and the means to enhance it. We evaluated the interplay of anodal transcranial direct current stimulation (atDCS) and Methylphenidate (MPH), both of which are known to alter cortical noise, a factor that can be measured by aperiodic exponents derived from EEG data. …”
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Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury by Aref Andishgar, Maziyar Rismani, Sina Bazmi, Zahra Mohammadi, Sedighe Hooshmandi, Behnam Kian, Amin Niakan, Reza Taheri, Hosseinali Khalili, Roohallah Alizadehsani

“…Nineteen variables were assessed using ML algorithms to predict outcomes. Data preparation addressed missing values and balancing methods corrected imbalances. …”
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