Predictive estimations of health systems resilience using machine learning by Alessandro Jatobá, Paula de Castro-Nunes, Paloma Palmieri, Omara Machado Araujo de Oliveira, Patricia Passos Simões, Valéria da Silva Fonseca, Paulo Victor Rodrigues de Carvalho

“…This research highlights the potential of ML in predictive modeling to inform strategic health decision-making, targeting interventions and more effective resource allocation. …”
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Optimizing Models and Data Denoising Algorithms for Power Load Forecasting by Yanxia Li, Ilyosbek Numonov Rakhimjon Ugli, Yuldashev Izzatillo Hakimjon Ugli, Taeo Lee, Tae-Kook Kim

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Link quality prediction based on random forest by Linlan LIU, Shengrong GAO, Jian SHU

“…Link quality prediction is vital to the upper layer protocol design of wireless sensor networks.Selecting high quality links with the help of link quality prediction mechanisms can improve data transmission reliability and network communication efficiency.The Gaussian mixture model algorithm based on unsupervised clustering was employed to divide the link quality level.Zero-phase component analysis (ZCA) whitening was applied to remove the correlation between samples.The mean and variance of signal to noise ratio,link quality indicator,and received signal strength indicator were taken as the estimation parameters of link quality,and a link quality estimation model was constructed by using a random forest classification algorithm.The random forest regression algorithm was used to build a link quality prediction model,which predicted the link quality level at the next moment.In different scenarios,comparing with exponentially weighted moving average,triangle metric,support vector regression and linear regression prediction models,the proposed prediction model has higher prediction accuracy.…”
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Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon by Muhammad Erwanto, Kosim Kosim, Nur Bambang Riyanto, Sukmo Banyu Jogo

“…This step is done by designing a system model that uses the C4.5 algorithm to form a decision tree to produce a rule for predicting student reading interest. …”
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Validation of a deep learning–based AI system for HER2-targeted breast cancer assessment using ultrasound imaging in a clinical setting by Kathryn Malherbe

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Deep learning for predicting the occurrence of tipping points by Chengzuo Zhuge, Jiawei Li, Wei Chen

“…Here, we address this challenge by developing a deep learning algorithm for predicting the occurrence of tipping points in untrained systems, by exploiting information about normal forms. …”
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Slipping Trend Prediction Based on Improved Informer by Jingchun Huang, Sheng He, Haoxiang Feng, Yongjiang Yu

“…The transformer-based Informer algorithm performs well in time series prediction and analysis. …”
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Modify possibilities of the secondary structures prediction method by Alvydas Špokas, Albertas Timinskas

“… It was analyzed dependence of the average accuracy of secondary protein structure prediction on various GOR algorithm modifications. In essence new modification has expanded informational parameter set by taking into account secondary structure of neighboring amino acid. …”
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Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace Applications by João P. Castanheira, Beltran N. Arribas, Rui Melicio, Paulo Gordo, André R. R. Silva

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Outcome prediction of the measles vaccination in healthcare employees by A. A. Ereshchenko, O. A. Gusyakova, N. B. Migacheva, F. N. Gilmiyarova, A. V. Lyamin

“…These models allowed to develop algorithm for predicting failures of the measles vaccination in healthcare workers that can be used for detection of persons at risk for non-forming specific humoral immunity. …”
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Explainable machine learning to predict the cost of capital by Niklas Bussmann, Paolo Giudici, Paolo Giudici, Alessandra Tanda, Alessandra Tanda, Ellen Pei-Yi Yu

“…Our findings pave the way for future investigations on the impact of ESG and country factors in predicting the cost of capital.…”
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Prediction of amphipathic helix-membrane interactions with Rosetta. by Alican Gulsevin, Jens Meiler

“…The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3Å of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. …”
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Application of federated learning in predicting breast cancer by Chai Jiarui

“…The prediction and diagnosis of breast cancer relies on multimodal data, such as imaging, genetic information, and patient lifestyle habits. …”
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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

“…This study aimed to develop and validate several predictive models for non-adherence, using patient-reported data collected via a structured questionnaire. …”
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The Prediction of the Compaction Curves and Energy of Bituminous Mixtures by Filippo Giammaria Praticò, Giusi Perri

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Comparing prediction efficiency in the BTW and Manna sandpiles by Denis Sapozhnikov, Alexander Shapoval, Mikhail Shnirman

“…The existence of the inactivity allows for the prediction of these events in advance. In this work, we explore the predictability of the Bak–Tang–Wiesenfeld (BTW) and Manna models on the square lattice as a function of the lattice length. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
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Machine Learning with Voting Committee for Frost Prediction by Vinícius Albuquerque de Almeida, Juliana Aparecida Anochi, José Roberto Rozante, Haroldo Fraga de Campos Velho

“…A machine learning (ML)-based methodology for predicting frosts was applied to the southern and southeastern regions of Brazil, as well as to other countries including Uruguay, Paraguay, northern Argentina, and southeastern Bolivia. …”
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Predicting surgical risk in morbidly obese patients by K. A. Anisimova, D. I. Vasilevsky, S. G. Balandov, E. T. Berulava, A. V. Zinchenko, N. V. Markov, I. G. Buhankov, E. V. Blinov, G. V. Semikova

“…The results obtained during the study made it possible to integrate the developed tactics of preoperative examination and preparation for surgical intervention in morbidly obese patients into a practical algorithm. Application of the developed tools for predicting the risk of complications in bariatric surgeries allowed to reduce the complication rate from 12.2 % to 2.0 %, and the mortality rate from 2.0 % to 0 %.CONCLUSION. …”
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Machine Learning for Health Insurance Prediction in Nigeria by Victor Enemona Ochigbo, Oluwasogo Adekunle Okunade, Emmanuel Gbenga Dada, Oluyemi Mikail Olaniyi, Oluwatoyosi Victoria Oyewande

“…This paper focused on predicting the likelihood of medical insurance coverage among individuals in Nigeria by employing four prominent Machine learning techniques: Logistic Regression, Random Forest, Decision Tree, and Support Vector Machine classifiers. …”
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