Review of open libraries for pharmacoeconomic analysis in R environment by I. A. Lackman, R. I. Sladkov, V. M. Timiryanova

“…The selected libraries can be divided into three classes: packages for calculating various quality of life indices, libraries for calculating indicators and indices of economic effectiveness of medical interventions (DALY, QALY, ICER), libraries for performing sensitivity analysis of the effect of medical interventions based on decision tree algorithms and Markov models. The libraries “heemod”, “hesim”, “rdesign” allow building simple Markov and semi-Markov models, but preference should be given to “heemod” due to the presence of vignettes. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…A lack of more extensive and consistent datasets was the most common issue, followed by the need to improve existing models.…”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…LAT incidence was assessed, and potential risk factors were analyzed. Machine learning algorithms, including decision tree, random forest, AdaBoost, k-Nearest Neighbor, and logistic regression, were employed to develop a predictive model for LAT. …”
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Synergistic Mechanisms Between Elderly Oriented Community Activity Space Morphology and Microclimate Performance: An Integrated Learning and Multi-Objective Optimization Approach by Fang Wen, Lu Zhang, Ling Jiang, Rui Tang, Bo Zhang

“…These findings provide quantitative guidelines for community space design in cold regions and offer data support for creating outdoor environments that meet the comfort needs of the elderly.…”
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Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand by Guangmei Yang, Guangdong Wang, Leping Wan, Xinle Wang, Yan He

“…To improve computational efficiency, we used three algorithms to develop prediction models, including Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Light Gradient Boosting Machine (LightGBM) algorithms. …”
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Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (<i>Annona squamosa</i> L.) by Xiangtai Jiang, Lutao Gao, Xingang Xu, Wenbiao Wu, Guijun Yang, Yang Meng, Haikuan Feng, Yafeng Li, Hanyu Xue, Tianen Chen

“…One of the most important nutrients needed for fruit tree growth is nitrogen. For orchards to get targeted, well-informed nitrogen fertilizer, accurate, large-scale, real-time monitoring, and assessment of nitrogen nutrition is essential. …”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…Using demographic, clinical and laboratory data of the patients, six different machine learning algorithms (SVM, KNN, ANN, Decision Tree, Naive Bayes and Discriminant Analysis) were used for classification. …”
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An Enhanced Machine Learning Framework for Type 2 Diabetes Classification Using Imbalanced Data with Missing Values by Kumarmangal Roy, Muneer Ahmad, Kinza Waqar, Kirthanaah Priyaah, Jamel Nebhen, Sultan S Alshamrani, Muhammad Ahsan Raza, Ihsan Ali

“…Consequently, the study validated the implications of these imputations using various classification algorithms, i.e., linear, tree-based, and ensemble algorithms, to see how each method affected classification accuracy. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…One key challenge is the need for efficient Handover (HO) optimization processes. …”
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Impact of Petty Tyranny on Employee Turnover Intentions: The Mediating Roles of Toxic Workplace Environment and Emotional Exhaustion in Academia by Javed Iqbal, Zarqa Farooq Hashmi, Muhammad Zaheer Asghar, Attiq Ur Rehman, Hanna Järvenoja

“…Similarly, results from the performance comparison of various algorithms reveal trade-offs between precision, recall, and processing time, with ZeroR and Stacking REP Tree emerging as the most effective in terms of overall model accuracy. …”
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Big Data Analytics in IoT, social media, NLP, and information security: trends, challenges, and applications by Kamal Taha

“…The taxonomy and experiments collectively demonstrate the need for context-aware algorithm selection, particularly for real-time and scalable Big Data applications. …”
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Deep‐HH: A deep learning‐based high school student hidden hunger risk prediction system by Yang Yang, Zheng Zhang, Huake Cao, Yuchen Zhang, Minao Wang, Ning Zhang

“…After quality control, we designated 632 students from Xuancheng City as the external test cohort and used the remaining 6477 students as the training cohort to develop predictive models. We used six ML algorithms (i.e., deep‐learning neural network [DNN], random forest, support vector machine, extreme gradient boosting, gradient boosting decision tree, and k‐nearest neighbor) to fit the training set using five‐fold cross‐validation, with hyperparameter tuning performed via Bayesian optimization. …”
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Phasic and periodic change of drought under greenhouse effect by Yang Li, Zhicheng Zheng, Yaochen Qin, Haifeng Tian, Zhixiang Xie, Peijun Rong

“…Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. …”
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Optimizing Random Forest Parameters with Hyperparameter Tuning for Classifying School-Age KIP Eligibility in West Java by Silfiana Lis Setyowati, Asyifah Qalbi, Rafika Aristawidya, Bagus Sartono, Aulia Rizki Firdawanti

“…Random Forest is an ensemble learning algorithm that combines multiple decision trees to generate a more stable and accurate classification model. …”
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The PM_2.5-Bound Polycyclic Aromatic Hydrocarbon Behavior in Indoor and Outdoor Environments, Part III: Role of Environmental Settings in Elevating Indoor Concentrations... by Gordana Jovanović, Mirjana Perišić, Timea Bezdan, Svetlana Stanišić, Kristina Radusin, Aleksandar Popović, Andreja Stojić

“…We applied seven regression tree ensemble algorithms to interrelate the variables alongside six metaheuristic optimization algorithms to refine model accuracy and robustness. …”
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Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…To meet the practical needs of urban green space planning and management, this research conducts digital simulations of the geometric forms and attribute information of green space plants, and proposes directions for further improvement of green space information models, including the construction of modeling standards, the development of sharing platforms, and the research on generative algorithms.ResultsThe structures and characteristics of green space plants differ from those of other urban components, and their digital representation methods need to be explored based on the spatial morphological features of the vegetation in green spaces. …”
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Intelligent design of mixture proportions of manufactured sand concrete from environmental, economical and mechanical perspectives by Junfei Zhang, Changhai Xu, Lei Zhang, Ling Wang

“…This study proposes a multi-objective optimization (MOO) method based on machine learning (ML) and the non-dominated sorting genetic algorithm II (NSGA-II) to optimize MSC mixtures. The results indicate that the extremely randomized trees (ERT) model exhibits the best predictive performance for UCS, with an R value of 0.988 on the test set. …”
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Carbon estimation of old-growth bald cypress knees using mobile LiDAR by Titilayo T. Tajudeen, Leah C. Rathbun, Leah C. Rathbun, Marcelo Ardón, Helena Mitasova

“…The volume of individual tree knees was estimated using multiple geometric algorithms and compared to allometric estimates from traditional field measurements derived from the shape of a cone. …”
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Pretreatment HIV‐1 Drug Resistance Among Newly Diagnosed People in Eastern Ethiopia by Abdella Gemechu, Adane Mihret, Mesfin Mengesha, Dawit Hailu Alemayehu, Eleni Kidane, Abraham Aseffa, Rawleigh Howe, Berhanu Seyoum, Andargachew Mulu

“…DRM profiles were examined and interpreted according to the calibrated population resistance (CPR) and Stanford University HIV drug resistance algorithms. A maximum likelihood phylogenetic tree was constructed using PhyML version 3.0 and visualized using the iTOL tool. …”
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