Problematic points of anticoagulant therapy for atrial fibrillation in certain Russian regions in 2016- 2019: results of a retrospective big data analysis by M. A. Druzhilov, O. Yu. Druzhilova, Z. A. Ilchenko, P. I. Chalaya, T. Yu. Kuznetsova

“…Despite its growth with a CHA2DS2-VASc score increase in the high-risk range, it did not comply with current clinical guidelines This specifies the need for stricter control over the implementation of treatment and diagnostic algorithms and local protocols for managing these patients.…”
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Iris: A Next Generation Digital Pathology Rendering Engine by Ryan Erik Landvater, Ulysses Balis

“…Iris Core comprises machine code modules written from the ground up in C++ and using Vulkan, a low-level and low-overhead cross-platform graphical processing unit application program interface, and our novel rapid tile buffering algorithms. We provide a detailed explanation of Iris Core's system architecture, including the stateless isolation of core processes, interprocess communication paradigms, and explicit synchronization paradigms that provide powerful control over the graphical processing unit. …”
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Cognitive approach to developing the intelligent modules of organizational and technical systems by V. M. Trembach

“…A widely used computing paradigm contains inherent symbolic submissions of information and their processing with algorithms focused on the logic and combinatorics of procedures. …”
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Predicting the risk of depression in older adults with disability using machine learning: an analysis based on CHARLS data by Tongtong Jin, Ayitijiang· Halili

“…A three-stage serial consensus approach feature selection framework (LASSO, Elastic Net, and Boruta) was employed to identify 21 robust predictors from 74 candidate variables. Ten ML algorithms were evaluated: LR, HistGBM, MLP, XGBoost, bagging, DT, LightGBM, RF, SVM, and CatBoost. …”
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An immunoinformatic investigation on Rift Valley fever virus protein reveals possible epitopes for vaccines by Tanjir Hosen, Saaimatul Huq, Mohammad Abdullah-Al-Shoeb, Shahidul Islam, Muhammad Abul Kalam Azad

“…Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T-cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively. …”
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Shedding light on the DICER1 mutational spectrum of uncertain significance in malignant neoplasms by D. S. Bug, I. S. Moiseev, Yu. B. Porozov, Yu. B. Porozov, N. V. Petukhova

“…The latest contemporary methods of variant effect prediction utilize machine learning algorithms on bulk data, yielding suboptimal correlation with biological data. …”
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Structural and social determinants of health: The multi-ethnic study of atherosclerosis. by Lilah M Besser, Sarah N Forrester, Milla Arabadjian, Michael P Bancks, Margaret Culkin, Kathleen M Hayden, Elaine T Le, Isabelle Pierre-Louis, Jana A Hirsch

“…Forty-seven (11%) of the papers combined MESA with other cohorts for cross-cohort comparisons and replication/validation (e.g., validating algorithms).<h4>Conclusions</h4>Overall, MESA has made significant contributions to the field and the published literature, with 20% of its published papers focused on SSDOH. …”
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Utilizing machine learning models for predicting outcomes in acute pancreatitis: development and validation in three retrospective cohorts by Kaier Gu, Yang Liu

“…In the training set, key variables were screened using univariate logistic regression and the LASSO method. Six ML algorithms were employed to construct predictive models. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Hybrid models combine the strengths of different algorithms, achieving 80–90% accuracy on average, and are particularly effective in complex, multi-faceted projects. …”
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Machine Learning Modeling of Foam Concrete Performance: Predicting Mechanical Strength and Thermal Conductivity from Material Compositions by Leifa Li, Wangwen Sun, Askar Ayti, Wangping Chen, Zhuangzhuang Liu, Lauren Y. Gómez-Zamorano

“…To overcome the limitations of traditional empirical models in capturing complex nonlinear relationships, a predictive framework with eight machine learning algorithms was established. Among these, Neural Network Regression exhibited the highest accuracy for mechanical property prediction, with a coefficient of determination of R² = 0.987 for compressive strength and R² = 0.932 for flexural strength. …”
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Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk by Ji-Eun Song, Ji Young Jang, Kyung Nam Kang, Ji Soo Jung, Chul Woo Kim, Ah Sol Kim

“…We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. …”
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Uncovering active ingredients and mechanisms of Pholiota adiposa in the treatment of Alzheimer’s disease based on network pharmacology and bioinformatics by Ma Xiaoying, Huo Zhiming, Shi Mingwen, Wang Hong, Yang Tao, Xiao Jun, Gong Na

“…LASSO regression and random forest algorithms were applied for target model selection, and molecular dynamics simulations were run with Gromacs2022.3. …”
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Synergistic use of SAR satellites with deep learning model interpolation for investigating of active landslides in Cuenca, Ecuador by Mohammad Amin Khalili, Silvio Coda, Domenico Calcaterra, Diego Di Martire

“…To this aim, we have used Long-Short Term Memory (LSTM) and Convolutional Neural Networks (CNN) as two different Deep Learning Algorithms (DLAs) to integrate results in the temporal and spatial domain, respectively. …”
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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure by Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

“…Research in spatial epidemiology relies on both conventional approaches and Machine- Learning (ML) algorithms to explore geographic patterns of diseases and identify influential factors (Pfeiffer & Stevens, 2015). …”
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The use of culturally adapted and translated depression screening questionnaires with South Asian haemodialysis patients in England. by Shivani Sharma, Sam Norton, Kamaldeep Bhui, Roisin Mooney, Emma Caton, Tarun Bansal, Clara Day, Andrew Davenport, Neill Duncan, Philip A Kalra, Maria Da Silva-Gane, Gurch Randhawa, Graham Warwick, David Wellsted, Magdi Yaqoob, Ken Farrington

“…However, data indicate that standard cut-off scores may not be appropriate to classify symptom severity. Use of the CIS-R algorithms for optimal case identification requires further exploration in this setting. …”
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Solar background radiation temperature calibration of a pure rotational Raman lidar by V. Jayaweera, R. J. Sica, G. Martucci, A. Haefele, A. Haefele

“…Furthermore, the technique works for temperature retrievals using both the optimal estimation method and the traditional temperature algorithms.</p>…”
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Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence by Pragya, A. Amalin Prince, Jac Fredo Agastinose Ronickom

“…Similarly, the drugs were described by Morgan, RDKit, and PubChem descriptors. We used AI algorithms like random forest regressor (RFR), extreme gradient boost regressor (XGBR), and one-dimensional convolutional neural network (1D-CNN) to predict the binding affinity. …”
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Use machine learning to predict treatment outcome of early childhood caries by Yafei Wu, Maoni Jia, Ya Fang, Duangporn Duangthip, Chun Hung Chu, Sherry Shiqian Gao

“…Methods This study was a secondary analysis of a recently published clinical trial that recruited 1,070 children aged 3- to 4-year-old with ECC. Machine learning algorithms including Naive Bayes, logistic regression, decision tree, random forest, support vector machine, and extreme gradient boosting were adopted to predict the caries-arresting outcome of ECC at 30-month follow-up after receiving fluoride and silver therapy. …”
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Identifying COVID-19-Infected Segments in Lung CT Scan Through Two Innovative Artificial Intelligence-Based Transformer Models by Zeinab Momeni pour, Ali Asghar Beheshti Shirazi

“… Introduction: Automatic systems based on Artificial intelligence (AI) algorithms have made significant advancements across various domains, most notably in the field of medicine. …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…Co-alignment was applied to multi-temporal UAV datasets, and tree segmentation was performed using the algorithms developed for Airborne Laser Scanning (ASL) forest point clouds. …”
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