THE FORMATION AND DEVELOPMENT OF CORPORATE CULTURE OF THE MEDICAL ORGANIZATIONS by O. L. Zadvornaya, V. Alekseev, K. Borisov

“…The results of the study indicate the need for concept development, tools implementation and development of corporate culture in the practice of the medical organizations.Conclusions/Significance: Corporate culture – the system of collectively shared values, symbols, beliefs, standards of behaviour employees of the organization that contributes to the originality and uniqueness of the activities of medical organizations that promote the identification of employees with the organization; Corporate culture is formed with the influence of factors external and internal environment of the organization, solving problems, external adaptation  and internal integration in the environment; Generated and promoted by the corporate culture is an important management tool, creates strong competitive advantage, increases the social responsibility of medical institutions to the society and patients, improves the quality of medical activities; The presence of the corporate culture of the organization, a coherent system of values and behavior models allows us to improve policy development processes, internal communication, unity and team cohesion, to create a single vector of development of human resources to reduce employee turnover in your organization; Medical organizations need the formation of the concept, mechanisms of implementation and development of corporate culture in practice activities; The system of continuous professional education of managerial staff of health must ensure the implementation of educational programs in the field of formation and development of the corporate culture of healthcare organizations.…”
Get full text

Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…The research methods include data collection and processing, construction and optimization of ML models, and the application of a risk assessment framework. …”
Get full text

Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

“…Enrichment analyses were performed using the clusterProfiler package. Support vector machine-recursive feature elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) regression, implemented via the caret and glmnet packages in R, were used to select biomarkers. …”
Get full text

HeLa TI cell-based assay as a new approach to screen for chemicals able to reactivate the expression of epigenetically silenced genes. by Varvara Maksimova, Natalya Shalginskikh, Olga Vlasova, Olga Usalka, Anastasia Beizer, Polina Bugaeva, Dmitry Fedorov, Olga Lizogub, Ekaterina Lesovaya, Richard Katz, Gennady Belitsky, Kirill Kirsanov, Marianna Yakubovskaya

“…Screening of chemicals reactivating silent genes requires adequate systems mimicking whole-genome processes. We used a HeLa TSA-inducible cell population (HeLa TI cells) obtained by retroviral infection of a GFP-containing vector followed by several rounds of cell sorting for screening purposes. …”
Get full text

JASBO: Jaya Average Subtraction Based Optimization with Deep Learning Model for Multi-Classification of Infectious Disease from Unstructured Data by Vian Sabeeh, Ahmed Bahaaulddin A. Alwahhab, Ali Abdulmunim Ibrahim Al-kharaz

“…Additionally, character-based network features are extracted using Bi-LSTM model. Then, vector representation is concatenated with two separate character-level extractions from Bi-LSTM and CNN. …”
Get full text

Modeling the thermal inactivation of non-pathogenic and avian-pathogenic Escherichia coli in broiler mash feed with high initial moisture content using a lab-based circulating wate... by Michael Carroll, Pratima Adhikari, Kelley Wamsley, Cangliang Shen, Timothy Boltz

“…Summary: The Food Safety Modernization Act (FSMA) has stimulated the need for research into feed sanitation practices for feed producers, particularly breeder and backyard flocks. Feed can be a vector for poultry pathogens, such as Escherichia coli (E. coli) transmission to poultry, and appropriate feed manufacturing can help mitigate the feed pathogens with thermal treatments. …”
Get full text

Antimicrobial Activity and Phytochemical Profiling of Natural Plant Extracts for Biological Control of Wash Water in the Agri-Food Industry by Piotr Kanarek, Barbara Breza-Boruta, Marcin Stocki

“…Water used in cleaning processes within the agri-food industry can be a vector for post-harvest contaminants, thus contributing to cross-contamination. …”
Get full text

New joint estimation method for emissivity and temperature distribution based on a Kriged Marginalized Particle Filter: Application to simulated infrared thermal image sequences by Thibaud Toullier, Jean Dumoulin, Laurent Mevel

“…The proposed method is based on a dynamical state-space modeling for the temperature, where the state vector is assumed to be split into a dynamic component for the temperature and a stationary component representing the emissivity. …”
Get full text

Evaluation of Sentinel-2 Deep Resolution 3.0 Data for Winter Crop Identification and Organic Barley Yield Prediction by Milen Chanev, Ilina Kamenova, Petar Dimitrov, Lachezar Filchev

“…With the use of three-date spectral band stacks, the Random Forest (RF) and Support Vector Classification (SVC) methods were used to differentiate between wheat, barley, and rapeseed. …”
Get full text

Change of the geopolitical choice of independent Ukraine (current historical aspect) by Bogdan Levyk

“…The paper looks into the processes and conditions which led to the change of the geopolitical vector of Ukraine in the second decade of the 21st century. …”
Get full text

RESEARCH INTO THE AERODYNAMICS OF AIR FLOWS IN CYCLONES by V. Petrov, А. Аlеksashyn, S. Poznar

“…The lines of equal air flow velocities and their vector analogues were built, zones of maximum and minimum pressure on the cyclone elements were determined. …”
Get full text

Quantitative Prediction of Protein Content in Corn Kernel Based on Near-Infrared Spectroscopy by Chenlong Fan, Ying Liu, Tao Cui, Mengmeng Qiao, Yang Yu, Weijun Xie, Yuping Huang

“…The associated methods and theoretical foundation provide a scientific basis for the quality control and processing of maize.…”
Get full text

Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…In one experiment, Alkhatib et al. used Convolutional neural network (CNN) based deep trackers to track the median and sciatic nerve with a surprising accuracy of 0.87.2 Another study employed the same CNN model to locate and discriminate accurate images of sacrum, vertebral levels and intervertebral gaps during percutaneous spinal needle insertion.3 Another study used a different AI model called SVM (support vector machine) classification, image processing, and template matching to locate lumbar level L3-L4 and the ideal puncture site for epidural anaesthesia in real-time. …”
Get full text

D₂X: Depression Detection System Through X Using Hybrid Machine Learning by Thara Angskun, Suda Tipprasert, Atitthan Thippongtorn, Jitimon Angskun

“…The <inline-formula> <tex-math notation="LaTeX">$D_{2}\mathbb {X}$ </tex-math></inline-formula> processes various types of tweets, including text messages, emoticons, and images, using a hybrid machine learning approach that combines support vector machine and random forest techniques. …”
Get full text

Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…Detection of metastasis mentions, however, proved more challenging, with the best-performing models Support Vector Machine (SVM) and logistic regression achieving an F1-score of 81%. …”
Get full text

Testing the Applicability and Transferability of Data-Driven Geospatial Models for Predicting Soil Erosion in Vineyards by Tünde Takáts, László Pásztor, Mátyás Árvai, Gáspár Albert, János Mészáros

“…Soil loss was formerly modeled by USLE, thus providing non-observation-based reference datasets for the calibration of parcel-specific prediction models using various ML methods (Random Forest, eXtreme Gradient Boosting, Regularized Support Vector Machine with Linear Kernel), which is a well-established approach in digital soil mapping (DSM). …”
Get full text

Machine learning models for estimating the overall oil recovery of waterflooding operations in heterogenous reservoirs by Sayed Gomaa, Ahmed Ashraf Soliman, Mohamed Mansour, Fares Ashraf El Salamony, Khalaf G. Salem

“…In this paper, four machine learning models: artificial neural network (ANN), Random Forest (RF), K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM) are applied to estimate the overall oil recovery (R) of water flooding. …”
Get full text

Predicting Diabetes Mellitus with Machine Learning Techniques by Heba Ahmed Jassim, Omar R. Kadhim, Zahraa Khduair Taha, Johnny Koh Siaw Paw, Yaw Chong Tak, Tiong Sieh Kiong

“…However, the Support Vector Machine (SVM) model performs worse than all the above models at 96.36% and seems to struggle with the correct classification of less frequent instances. …”
Get full text

Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

“…Spectral data within the 398~1004 nm wavelength range were analyzed to compare the predictive performance of the Least Squares Support Vector Machine (LS-SVM) models on various quality parameters, using different preprocessing methods and the selected feature wavelengths. …”
Get full text

Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…For the classification phase, we chose three classification algorithms—MLP (Multilayer Perceptron), ELM (Extreme Learning Machine), and SVM (Support Vector Machine)—and performed a comprehensive comparison of their classification and generalisation abilities using grid search for hyperparameter optimisation and five-fold cross-validation. …”
Get full text