Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

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DeepInvesting: Stock market predictions with a sequence-oriented BiLSTM stacked model – A dataset case study of AMZN by Ashkan Safari, Mohammad Ali Badamchizadeh

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A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

Subjects: “…thickness prediction…”
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Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

Subjects: “…Heart-kidney algorithm…”
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Bridging the Gap Between Machine Learning and Medicine: A Critical Evaluation of the Dworak Regression Grade in Rectal Cancer by Camille Raets, Chaimae El Aisati, Amir L. Rifi, Mark De Ridder, Koen Putman, Johan De Mey, Alexandra Sermeus, Kurt Barbe

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Non – Invasive, smartphone image-based screening for sickle cell disease at the point-of-need by Eudorah F. Vital, Meredith Haak LiCalzi, Robert G. Mannino, Patrick T. McGann, Wilbur A. Lam

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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

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Opportunities of machine learning algorithms for education by Olga Ovtšarenko

“…This study explores the potential of machine learning algorithms to build and train models using log data from the "3D Modeling" e-course on the Moodle platform at TTK University of Applied Sciences, Tallinn, Estonia. …”
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Nonvariational ADAPT algorithm for quantum simulations by Ho Lun Tang, Yanzhu Chen, Prakriti Biswas, Alicia B. Magann, Christian Arenz, Sophia E. Economou

“…We compare this nonvariational algorithm with ADAPT-VQE and with feedback-based quantum algorithms in terms of the rate of energy reduction, the circuit depth, and the measurement cost in molecular simulation. …”
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FCC algorithm for power loss diminution by Kanagasabai L.

“…In this work, the FCC algorithm has been applied to the power problem. Real power loss reduction, voltage deviation minimization, and voltage stability enhancement are the key objectives of the proposed work. …”
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Computational complexity, algorithmic scope, and evolution by Leonhard Sidl, Maximilian Faissner, Manuel Uhlir, Cristian A Velandia-Huerto, Maria Waldl, Hua-Ting Yao, Ivo L Hofacker, Peter F Stadler

“…We use RNA secondary structure prediction as a simple surrogate for developmental programs to demonstrate that the salient features of the genotype–phenotype map remain intact even if ‘simpler’ algorithms are employed that correctly compute the structures only for small subsets of instances, albeit quantitative differences depending on the choice of alternative algorithms can be observed.…”
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Optimal Power Generation from Bagasse in a Sugarcane Plant using PSO Algorithm Compared to SQP Algorithm by Mohammad Askari Khanabadi, Imaneh Dehghani, Shahrokh Shojaeian

“…Due to the high amounts of sugarcane residue or bagasse which was produced by sugarcane plants in Iran, this study was aimed to optimize power generation from bagasse biomass in sugarcane plants using Particle Swarm Optimization (PSO) algorithm by data obtained from several case studies which had been simulated with SQP (Sequential quadratic programming) algorithm. …”
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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes by Himan Shahabi, Ataollah Shirzadi, Alicja Ustrzycka, Natalia Piotrowska, Janusz Filipiak, Marzieh Hajizadeh Tahan

Subjects: “…Carbon-13 predicting…”
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Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

“…Consequently, Emperor Penguins Colony (EPC) optimization algorithm was also employed for selecting the essential features, which reduces the data dimensionality and assists the predictive algorithm to focus on important features in its training phase. …”
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Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…Deep-learning neural networks optimized with the Levenberg-Marquardt algorithm (DLNNs-LMA) is a supervised AI-based approach that is used to analyze the Eyring Powell fluid in a two-phase flow (EPFM-TPF) with dust particles and at temperature-dependent viscosity. …”
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Novel disctete grey Bernoulli seasonal model with a time powter term for predicting monthly carbon dioxide emissions in the United States by Jianming Jiang, Yandong Ban, Sheng Nong

“…This study proposes a more efficient discrete grey prediction model to describe the seasonalvariation trends of carbon dioxide emissions. …”
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Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun, Kun Yang

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ANN-based pulse shape discrimination for background reduction in neutron depth profiling by Hwijoon Jeong, Jinhwan Kim, Byung Gun Park, Kyung Taek Lim

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Making predictions for overhead power lines applying predictive analytics by Yu. N. Kondrashova, A. M. Tretyakovͬ, A. V. Shalimov

“…It should be noted that the general trend is a high percentage of wear and tear, moral and physical aging of the main and auxiliary electrical equipment.Goal - the application of methods of mathematical analysis and predictive analytics to predict the number of failures of electrical equipment and the development of an algorithm for calculating forecasting to assess damages in the future.Materials and methods. …”
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