An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…Machine learning (ML) approaches have emerged as a promising technique to predict structural similarity from MS/MS that may surpass the current state-of-the-art algorithmic methods. However, the comparison between these different ML methods remains a challenge because there is a lack of standardization to benchmark, evaluate, and compare MS/MS similarity methods, and there are no methods that address data leakage between training and test data in order to analyze model generalizability. …”
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Correspondence distribution over a network in designing public urban passenger transportation tasks by A. I. Fadeev, A. M. Iliankov, V. V. Ukaderov

“…The formation acceptable routes on the transport network can be carried out by means of the algorithms developed, for example, in the framework of solving TNDP and TNDFSP tasks. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…The vast majority of marine seabed priority habitats in the study area appeared to fall outside the borders of the current Natura 2000 sites, which served as the baseline for the declared trawl bans in Greek waters, following the provisions of the EU Marine Action Plan.…”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
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Athletic Pubalgia – A Significant Diagnostic and Therapeutic Challenge in Athletes? by Adam Jan Ząbek, Jakub Paweł Kuźniar, Emilia Gabriela Chrzanowska, Michalina Zagalska, Marta Turek, Tomasz Tamborski, Adam Grzebinoga, Julia Szlążek, Barbara Roguska, Karolina Maria Mitręga

“…Further clinical studies are needed to develop standardized diagnostic and therapeutic algorithms. …”
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Dilated cardiomyopathy evaluation with Imagenomics: combining multimodal cardiovascular imaging and genetics by Kristian Galanti, Ghaith Sharaf Dabbagh, Fabrizio Ricci, Sabina Gallina, Roberta Giansante, Ron Jacob, Edmond Obeng‐Gyimah, Leslie T. Cooper Jr, Sanjay K. Prasad, David H. Birnie, Andrew P. Landstrom, Selma F. Mohammed, Saidi Mohiddin, Mohammed Y. Khanji, Anwar A. Chahal

“…Also, we strive to qualify the role of cardiac imaging in the diagnosis of DCM, particularly on the relevance of novel techniques and clinical utility of actionable parameters to improve current diagnostic schemes and risk stratification algorithms. …”
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Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy by D. Quint, D. Quint, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, N. Bodini, D. Rosencrans

“…<p>Offshore wind energy projects are currently in development off the east coast of the United States and may influence the local meteorology of the region. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…The results show that random forest and ensemble learning algorithms delivered the highest predictive accuracy, evidenced by the most substantial coefficient of determination (R2) and minimal error metrics. …”
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Decentralized multi-agent federated and reinforcement learning for smart water management and disaster response by H. Mancy, Naglaa E. Ghannam, Amr Abozeid, Ahmed I. Taloba

“…The proposed FL-MAPPO model surpasses current methods by facilitating decentralized, privacy-protecting decision-making minimizing latency and single-point failures. …”
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Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts by Emre Uysal, Gorkem Durak, Ayse Kotek Sedef, Ulas Bagci, Tanju Berber, Necla Gurdal, Berna Akkus Yildirim

“…<b>Background/Objectives</b>: Current developments in computer-aided systems rely heavily on complex and computationally intensive algorithms. …”
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Reducing the acquisition time for magnetic resonance imaging using super-resolution image generation and evaluating the accuracy of hippocampal volumes for diagnosing Alzheimer’s d... by Nobukiyo Yoshida, Nobukiyo Yoshida, Hajime Kageyama, Hajime Kageyama, Hiroyuki Akai, Satoshi Kasai, Satoshi Kasai, Kei Sasaki, Noriko Sakurai, Naoki Kodama

“…IntroductionBrain magnetic resonance imaging (MRI) is important for diagnosing Alzheimer’s disease (AD), and MRI acquisition time should be reduced. The current study aimed to identify which Pix2Pix-based super-resolution images can reduce errors associated with brain anatomical analysis with diffeomorphic deformation examination and MRI acquisition time.MethodsFifty patients with dementia who uderwent scanning using a 3-T MRI scanner in the OASIS-3 database were used to construct a super-resolution network. …”
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Synergizing remote sensing, support vector machine, and aeromagnetic data for precise lithological and mineral potential mapping: a case study from Egypt by Hatem M. El-Desoky, Ahmed M. Abdel-Rahman, Hamada El-Awny, Wael Fahmy, Reda Abdu Yousef El-Qassas, Kamal Abdelrahman, Hassan Alzahrani, Peter Andráš, Yahia Z. Amer, Ahmed M. Eldosouky

“…Therefore, we effectively mapped the exposed rock units in the Hamash region of the Eastern Desert of Egypt by using Support Vector Machine (SVM) to Sentinel 2 data through executing machine learning algorithms (MLAs). This goal involves extensive fieldwork, petrographical examinations, and image processing remote sensing techniques to accurately reveal the exposed lithologies distribution besides the potential relic areas. …”
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Enhancing forest biodiversity indicators in inventories through harmonized protocols by Moreno-Fernández D, Breidenbach J, Cañellas I, Chirici G, D’Amico G, Ferretti M, Giannetti F, Puliti S, Schnell S, Shackleton R, Skudnik M, Alberdi I

“…Once the bird and mammal data have been collected, advanced algorithms could facilitate and enhance the efficiency of the analyses. …”
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Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities by Yayuan Xia, Linhui Li, Peipei Liu, Tianxu Zhai, Yibing Shi

“…Abstract Objective The purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic stroke (AIS). …”
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AI-powered visual E-monitoring system for cattle health and wealth by Aung Si Thu Moe, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin

“…Through integrated deep learning algorithms, the platform performs key health-related tasks, including ear-tag, body-based, and face-based cattle identification, body condition scoring (BCS), lameness detection, feeding time estimation, and real-time localization. …”
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Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

“…Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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A Comparative Study of the Accuracy and Readability of Responses from Four Generative AI Models to COVID-19-Related Questions by Zongjing Liang, Yun Kuang, Xiaobo Liang, Gongcheng Liang, Zhijie Li

“…Then the neural network model in the intelligent algorithms is used to identify the factors that affect readability. …”
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The photometry and kinematics studies of NGC 2509 derived from Gaia DR3 by Nasser M. Ahmed, A. L. Tadross

“…We employed the pyUPMASK Python package and HDBSCAN algorithms to identify the cluster member stars. The current analysis introduces a new method that connects the membership probability of stars in the cluster (using the pyUPMASK tool) with the number of stars predicted by the King model at different distances from the center of the cluster. …”
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Co-occurrence of sudden feeding behaviour deviations and welfare issue onsets in growing-finishing pigs by Jacinta D. Bus, Rudi M. de Mol, Laura E. Webb, Eddie A. M. Bokkers, Iris J. M. M. Boumans

“…Abstract Background Modern sensor technologies and algorithms have the potential to continuously monitor indicators of individual animal welfare, but in growing-finishing pigs the validity of such welfare monitoring remains low for unclear reasons. …”
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Prediction of Flexural Ultimate Capacity for Reinforced UHPC Beams Using Ensemble Learning and SHAP Method by Zhe Zhang, Xuemei Zhou, Ping Zhu, Zhaochao Li, Yichuan Wang

“…Furthermore, multiple machine learning (ML) algorithms, including both traditional and EL models, are employed to develop optimized predictive models for the flexural ultimate capacity of reinforced UHPC specimens derived from the established database. …”
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