Design of a Manned-Unmanned Teaming System and Forward-Formation Control for Crevasse Detection in the Path of a Human-Driven Vehicle by Ji-Wook Kwon, Hyoujun Lee, Taeyoung Uhm, Jongdeuk Lee, Na-Hyun Lee, Young-Ho Choi

“…The stability and performance of the proposed MUM-T system, forward-formation, and motion control algorithm are validated through simulations. Especially, the forward-formation demonstrated more than an 86% improvement in predicting and mimicking the leader’s trajectory compared to conventional formation strategies. …”
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Remote Management of Heart Failure in Patients with Implantable Devices by Luca Santini, Francesco Adamo, Karim Mahfouz, Carlo Colaiaco, Ilaria Finamora, Carmine De Lucia, Nicola Danisi, Stefania Gentile, Claudia Sorrentino, Maria Grazia Romano, Luca Sangiovanni, Alessio Nardini, Fabrizio Ammirati

“…<b>Results</b>: Precise multi-parameter algorithms, available for ICD and CRT-D patients, have been created, which also use artificial intelligence and are able to predict a new heart failure event more than 30 days in advance. …”
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Heart transplantation and COVID-19 in the early postoperative period in hypertrophic cardiomyopathy: a clinical case by M. R. Zaynetdinov, M. N. Mukharyamov, R. K. Dzhordzhikiya, I. I. Vagizov, M. A. Miroshnichenko, I. V. Abdulyanov, R. R. Khamzin, D. I. Abdulganieva, E. V. Dyakova, A. Zh. Bayalieva, N. F. Gizatullina, N. Yu. Stekolshchikova, M. M. Minnullin, R. N. Khairullin

“…It does not have clearly developed surgical correction algorithms. Heart transplantation (HTx) is the sole therapeutic option when drug therapy is ineffective and surgical reduction of hypertrophic myocardium is not feasible. …”
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HUMAN BODY ANTHROPOMORPHIC PHANTOM UTILISATION FOR THE COMPLEX TESTING OF RADIATION THERAPY TECHNOLOGICAL PROCESS by Y. I. Holdman, E. V. Titovich

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Text mining of hypertension researches in the west Asia region: a 12-year trend analysis by Mohammad Rezapour, Mohsen Yazdinejad, Faezeh Rajabi Kouchi, Masoomeh Habibi Baghi, Zahra Khorrami, Morteza Khavanin Zadeh, Elmira Pourbaghi, Hassan Rezapour

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A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

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Model of electromagnetic field effect on biological tissues. by Р. V. Kamlach, D. S. Hroda, A. V. Churakov, V. I. Kamlach, V. М. Bondarik, S. I. Madveika, A. P. Klyuev

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The Spatial and Dynamic Monitoring in Ensuring the Management of Energy Security of Enterprises by Budanov Mykola P.

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Design of a discrete сosine transformation processor for image compression systems on a losless-to-lossy circuit by V. V. Kliuchenia

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COMPLEXING IMAGES IN A TWO-CHANNEL OPTICAL-ELECTRONIC SYSTEM AS A METHOD OF REDUCING THE PROBABILITY OF DISAPPOINTING AN AUTOMATIC SURVEILLANCE OF LOW CONTRAST OBJECTS by A. V. Khizhniak

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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin by Fei Tian, Wenhao Zheng, Aosai Zhao, Jingyue Liu, Yunchen Liu, Hui Zhou, Wenjing Cao

“…This model incorporates select seismic attributes and leverages fusion algorithms like K-means, ellipsoid growth, and wavelet transformations. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. …”
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A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review by Ivan Maleš, Marko Kumrić, Andrea Huić Maleš, Ivan Cvitković, Roko Šantić, Zenon Pogorelić, Joško Božić

“…In diagnostics, ML algorithms incorporating clinical, laboratory, imaging, and demographic data have improved accuracy and reduced uncertainty. …”
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Literature Review of Prognostic Factors in Secondary Generalized Peritonitis by Valerii Luțenco, Adrian Beznea, Raul Mihailov, George Țocu, Verginia Luțenco, Oana Mariana Mihailov, Mihaela Patriciu, Grigore Pascaru, Liliana Baroiu

“…Emerging evidence suggests that machine learning algorithms may improve early risk stratification and individualized outcome prediction when integrated with conventional scoring systems. …”
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Quantifying the Geomorphological Susceptibility of the Piping Erosion in Loess Using LiDAR-Derived DEM and Machine Learning Methods by Sisi Li, Sheng Hu, Lin Wang, Fanyu Zhang, Ninglian Wang, Songbai Wu, Xingang Wang, Zongda Jiang

“…The results showed that all six of these machine learning algorithms had an AUC of more than 0.85. The GBDT model had the best predictive accuracy (AUC = 0.94) and model migration performance (AUC = 0.93), and it could find sinkholes with high and very high susceptibility levels in loess areas. …”
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Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…With big data, it also allows us to reduce computational time, improve prediction performance, and better understand the data in machine learning or pattern recognition applications. …”
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Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms.…”
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Discovering New Tyrosinase Inhibitors by Using In Silico Modelling, Molecular Docking, and Molecular Dynamics by Kevin A. OréMaldonado, Sebastián A. Cuesta, José R. Mora, Marcos A. Loroño, José L. Paz

“…<b>Background/Objectives:</b> This study was used in silico modelling to search for potential tyrosinase protein inhibitors from a database of different core structures for IC₅₀ prediction. <b>Methods</b>: Four machine learning algorithms and topographical descriptors were tested for model construction. …”
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Unravelling Antimicrobial Resistance in <i>Mycoplasma hyopneumoniae</i>: Genetic Mechanisms and Future Directions by Raziallah Jafari Jozani, Mauida F. Hasoon Al Khallawi, Darren Trott, Kiro Petrovski, Wai Yee Low, Farhid Hemmatzadeh

“…Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. …”
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