Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency by Jonathan Tarquino, Jhonathan Rodríguez, David Becerra, Lucia Roa-Peña, Eduardo Romero

“…This assessment is still manually performed by trained specialists, who may be a bottleneck within the clinical process. Deep learning algorithms are a promising approach to automate this bone marrow cell evaluation. …”
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Risk factors for tuberculosis treatment outcomes: a statistical learning-based exploration using the SINAN database with incomplete observations by Nguyen Ky Phat, Yoonah Lee, Dinh Hoa Vu, Nguyen Phuoc Long, Seongoh Park

“…Methods We exploited the upweighting approach and multiple imputation analysis (MIA) to address the extreme imbalance in responses and missing data. Three algorithms were employed for TB treatment outcome prediction, including logistic regression (LOGIT), random forest, and stochastic gradient boosting. …”
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Comprehensive bioinformatics analysis of the common mechanism of atherosclerosis and atrial fibrillation: emphasizing mitochondrial metabolic disorder and immune inflammation by Rui Dai, Xiaotong Lei, Xiaojun Liu, Chen Bian

“…Three machine learning algorithms (LASSO, SVM, and random forest) were applied to screen hub genes, followed by validation in independent datasets. …”
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Modern strategies of alternative insulin delivery systems by І. О. Vlasenko, L. L. Davtian, V. V. Hladyshev

“…Innovations in alternative insulin delivery systems include algorithms for continuous glucose monitoring systems, glucose-sensitive polymer matrices and biological structures with insulin. …”
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Investigating ethical tradeoffs in crisis standards of care through simulation of ventilator allocation protocols. by Jonathan Herington, Jessica Shand, Jeanne Holden-Wiltse, Anthony Corbett, Richard Dees, Chin-Lin Ching, Margie Shaw, Xueya Cai, Martin Zand

“…Unlike other protocols, the New York and Maryland algorithms did not generate significant disparities in lives saved and life-years saved between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. …”
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AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

“…The framework integrates machine learning (ML) algorithms for predictive temperature management, blockchain technology for secure data handling, and edge computing for real-time data processing, resulting in a highly efficient and secure system. …”
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Monotonicity Criterion-Based Power Quality Improvement in Distributed Energy Systems with Solar PV Integration by Phani Kumar Chittala, Elanchezhian E.B, Pragaspathy Subramani, Subramanian S

“…The study highlights the potential for advanced power electronics converters, high-frequency switching devices, active harmonic filters, grid-connected energy storage systems, and sophisticated control algorithms to achieve near-perfect power matching, even up to the 497th harmonic, despite non-linearities in network behavior and PV performance.…”
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Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory by Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore

“…Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. …”
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Metastatic bone lesions of men in combination with an increase in serum PSA from the point of view of diagnosing carcinomas of unknown primary localization by O. V. Poslavska, I. S. Shponka, P. O. Hritsenko, M. Yu. Petrova

“…The aim of the work is to improve diagnostic algorithms, to investigate a complex of morphological, morphometric and immunohistochemical characteristics of metastatic foci in the bones, which are represented by adenocarcinomas of unknown primary localization in men with increased serological marker PSA, compared with primary carcinomas of the prostate gland. …”
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The relationship between kinship and foster placement on mental health indicators in children and youth seeking treatment by Shannon L. Stewart, Boden Brock, Jordyn Manis, Aadhiya Vasudeva, Jeffrey W. Poss

“…These assessments include a variety of embedded evidence-informed scales and algorithms to examine the mental health needs, preferences and strengths of these vulnerable children. …”
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Identification of marker genes associated with oxidative stress in hypertrophic cardiomyopathy using bioinformatics analysis and experimental validation by Jian Zhuo, Ding Ding, Mengkang Fan, Weiwei Lu, Xiaochen Lu, Lihong Yao, Hongzhuan Sheng

“…After differential analysis, marker genes were obtained using LASSO and SVM-RFE algorithms. DAVID was used, along with the GSVA and GSEA packages to perform gene ontology, pathway function enrichment, and gene set enrichment analyses. …”
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DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification by Fei Pan, Dawei He, Pengjun Xiang, Mengdie Hu, Daizhuang Yang, Fang Huang, Changmeng Peng

“…Existing classification algorithms often suffer from limitations such as reliance on single information sources, constrained feature extraction capabilities, time consumption, low accuracy, and the potential to cause irreversible damage to seeds. …”
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Development and validation of a nomogram for predicting refractory peritoneal dialysis related peritonitis by Qiqi Yan, Guiling Liu, Ruifeng Wang, Dandan Li, Xiaoli Chen, Deguang Wang

“…Univariate logistic analysis, LASSO regression analysis, and random forest algorithms were utilized to identify the potential risk factors for refractory peritonitis. …”
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Anatomically Guided Deep Learning System for Right Internal Jugular Line (RIJL) Segmentation and Tip Localization in Chest X-Ray by Siyuan Wei, Liza Shrestha, Gabriel Melendez-Corres, Matthew S. Brown

“…To reduce the workload of clinicians, deep learning-based automated detection algorithms have been developed to detect CVCs in CXRs. …”
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Markov model of representation of sensual images for the formation of the model of the outside world by A. A. Solodov

“…In this regard, the further development of the model may be associated with the assessment of the probability of the system response to external influences, taking into account the characteristics of these specific signals, as well as the development of optimal algorithms for decision-making about the presence or absence of impacts on the system from the outside world.…”
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SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS by Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

“…In the study discussed here, different machine learning (ML) algorithms were investigated to foresee construction delays, and these include Gaussian Naïve Bayes, Adaboost, Logistic Regression, Gradient Boosting (GB), Random Forest (RF), Decision Tree (DT) and Extreme Gradient Boosting (XGBoost). …”
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Exploring the ceRNA network involving AGAP2-AS1 as a novel biomarker for preeclampsia by Fan Lu, Ni Zeng, Xiang Xiao, Xingxing Wang, Han Gong, Houkang Lei

“…Then candidate hub genes were obtained through five algorithms by the protein-protein intersection (PPI) network of the mRNAs. …”
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Downscaling air temperatures for high-resolution niche modeling in a valley of the Amazon lowland forests: A case study on the microclima R package. by M J Pohl, L Lehnert, B Thies, K Seeger, M B Berdugo, S R Gradstein, M Y Bader, J Bendix

“…Despite problems with the distinction between CAD and non-CAD events the microclima algorithms show difficulties in correctly modeling the diurnal course of the temperature data and the amplitudes of elevational temperature gradients. …”
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Characterizing and mapping the spatial variability of HIV risk among adolescent girls and young women: A cross-county analysis of population-based surveys in Eswatini, Haiti, and M... by Kristen N Brugh, Quinn Lewis, Cameron Haddad, Jon Kumaresan, Timothy Essam, Michelle S Li

“…Using geolocated survey data at enumeration clusters and high-resolution satellite imagery, we applied algorithms to predict the number and proportion of at-risk AGYW at hyperlocal levels.…”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Conclusion By effectively merging advanced neural network algorithms with conventional rainfall estimation methods, this study provides a robust framework for understanding and estimating precipitation in arid regions like the UAE. …”
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