Algorithms of Rickettsiae’s Detection and Laboratory Diagnosis of Rickettsioses of Spotted Fever Group in Russia by N. V. Rudakov, I. E. Samoylenko, L. V. Kumpan

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Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…Furthermore, moving past premature convergence provides more robust algorithms that can discover global optima. Moreover, the theoretical aspects of SI algorithms are still in their infancy and propose novel methods to improve predictability and reliability. …”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…The accuracy of these algorithms was evaluated based on their ability to correctly identify epochs, and their clinical reliability was assessed by comparing their predictions to those of clinicians with different levels of experience in asynchrony classification. …”
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Analysis of random factors of the self-education process by A. A. Solodov

“…The aim of the study is the statistical description of the random factors of the self-educationт process, namely that stage of the process of continuous education, in which there is no meaningful impact on the student’s educational organization and the development of algorithms for estimating these factors. …”
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Fault location and isolation technology for power grid automation based on intelligent algorithms by Qi Guo, Fuhe Wang, Suxia Cheng, Ke Wang, Yifan Zhang

“…Methodology The FLA algorithm uses a Support Vector Machine (SVM) classifier to predict fault locations based on key variables like voltage, current, frequency, line impedance, and meteorological conditions. …”
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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

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Using Grayscale Photos to Introduce High School Statistics Teachers to Reasoning with Digital Image Data by Anna Fergusson, Maxine Pfannkuch

Subjects: “…Algorithmic modeling…”
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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…Concurrently, long short-term memory (LSTM) models have shown considerable promise in enhancing air quality predictions, often outperforming other prediction techniques. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…Techniques for QML have the potential to forecast cardiac disease and help in early detection. To predict the risk of coronary heart disease, a hybrid approach utilising an ensemble machine learning model based on QML classifiers is presented in this paper. …”
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Development and validation of machine learning models predicting hospitalizations of hypertensive patients over 12 months by A. E. Andreychenko, A. D. Ermak, D. V. Gavrilov, R. E. Novitsky, O. M. Drapkina, A. V. Gusev

“…To develop models for predicting hospitalizations of hypertensive (HTN) over 12 months using machine learning algorithms and to validate them using real-world practice data.Material and methods. …”
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Lifetime Prediction of Power IGBT Module by WANG Yan-gang, Chamund Dinesh, LI Shi-ping, Jones Steve, DOU Ze-chun, XIN Lan-yuan, LIU Guo-you

“…The Weibull methodology for power cycling test data and some reported typical lifetime models were firstly discussed. Then, lifetime prediction procedures were presented including the conversion of mission profile to temperature profile, the temperature cycles counting by Rainflow algorithm, and lifetime calculating based on the fatigue linear accumulation damage theory and lifetime models. …”
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Genetic prediction of male pattern baldness. by Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni

“…By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. …”
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Conformational ensembles for protein structure prediction by Jiaan Yang, Wen Xiang Cheng, Peng Zhang, Gang Wu, Si Tong Sheng, Junjie Yang, Suwen Zhao, Qiyue Hu, Wenxin Ji, Qiong Shi

“…The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.…”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The machine learning algorithms can handle high-dimensional nonlinear data with complex interactions, outperform traditional statistical models in ecology, and have been effectively used for plant classification, phenology detection, crop growth detection, and yield prediction. …”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic by Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

“…We also present a model for predicting traffic accidents using categorical logic, creating a Knowledge Base using the Resolution algorithm as a proof of concept. …”
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Novel three‐dimensional ECG algorithm for reliable screening for cardiac amyloidosis by Amir A. Mahabadi, Jan Knobeloch, Viktoria Backmann, Lars Michel, Markus S. Anker, Reza Wakili, Christian Fach, Stefan D. Anker, Tienush Rassaf

“…In the derivation cohort, the AI algorithm reached a sensitivity of 85%, a specificity of 89%, a positive predictive value of 91%, and a negative predictive value of 87%. …”
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Ethical Norms for the Use of Artificial Intelligence in Education by Galya Kozhuharova, Mihail Kozhuharov

“…While these technologies promise more effective and accessible education, their application creates significant ethical challenges. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…Our novel approach, LGWO-BP, is tailored to augment the precision of cancer prognosis predictions. We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

“…Abstract State‐of‐the‐art model‐based predictive control techniques for AC motor drives are reviewed in this paper. …”
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