AI-Driven Gamification and Biotechnical Systems in Cardiovascular Monitoring of Cyclic Sport Athletes by Shukurova Sayyora, Pulatova Mavlyuda, Adilbekov Taxir

“…The paper attempts to move forward research in biotechnical systems and gamification from traditional sports medicine, athlete conditioning, and exercise physiology contexts to emerging AI-enhanced frameworks that address current cardiovascular health challenges.In proposing such a novel approach, the authors reason why AHP-regression-based studies may be particularly suited for the iterative assessment, validation, and optimization of findings in the form of decision-making models such as personalized AI-driven training algorithms. Additionally, the analytical hierarchy process (AHP) framework is used to organize a systematic evaluation of predictive modeling techniques to identify some best practices related to specific biométrie parameters and athlete performance metrics.This methodological application then furthers the examination of the physiological and computational implications related to the use of AI-driven cardiovascular monitoring in terms of accuracy, efficiency, and adaptability. …”
Get full text

Innovative data techniques for centrifugal pump optimization with machine learning and AI model. by Gaurav Sandeep Dave, Amar Pradeep Pandhare, Atul Prabhakar Kulkarni, Dhananjay Vasant Khankal

“…The validated data is employed to train machine learning classifiers and deep learning algorithms, targeting a 27.25% enhancement in operational efficiency based on F1 score. …”
Get full text

Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure by Ankita Sharma, Shalli Rani, Mohammad Shabaz

“…It incorporates AI-driven security models and anomaly detection algorithms to enhance grid resilience and optimize energy utilization. …”
Get full text

Mapping expanded prostate cancer index composite to EQ5D utilities to inform economic evaluations in prostate cancer: Secondary analysis of NRG/RTOG 0415. by Rahul Khairnar, Stephanie L Pugh, Howard M Sandler, W Robert Lee, Ester Villalonga Olives, C Daniel Mullins, Francis B Palumbo, Deborah W Bruner, Fadia T Shaya, Soren M Bentzen, Amit B Shah, Shawn C Malone, Jeff M Michalski, Ian S Dayes, Samantha A Seaward, Michele Albert, Adam D Currey, Thomas M Pisansky, Yuhchyau Chen, Eric M Horwitz, Albert S DeNittis, Felix Y Feng, Mark V Mishra

“…<h4>Conclusions</h4>This is the first study to identify a comprehensive set of mapping algorithms to generate EQ5D utilities from EPIC domain/ sub-domain scores. …”
Get full text

Automation of the Formation of a Mathematical Formulation of Kinetics for Multistage Chemical Reactions and Numerical Solution to a Direct Problem by N. A. Lysenko, K. F. Koledina

“…The direct kinetics problem was solved using algorithms: the Gear method, the Runge-Kutta method of the 4th order, and the scipy.odeint() method of the Python language. …”
Get full text

Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging – A systematic review and meta-analysis by Qiong Wu, Dimitra Kiakou, Karsten Mueller, Wolfgang Köhler, Matthias L. Schroeter

“…This study aims to assess the diagnostic and predictive efficacy of neuroimaging feature-based AI algorithms for FTLD. …”
Get full text

Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

“…ABSTRACT The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. …”
Get full text

Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…By extracting novel characteristics from diverse medical data sources, advanced identification techniques known as multimodal learning may be applied, enabling algorithms to analyze data from various sources and eliminating the need to train each modality. …”
Get full text

Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. …”
Get full text

Evaluating the Effect of Thermal Treatment on Phenolic Compounds in Functional Flours Using Vis–NIR–SWIR Spectroscopy: A Machine Learning Approach by Achilleas Panagiotis Zalidis, Nikolaos Tsakiridis, George Zalidis, Ioannis Mourtzinos, Konstantinos Gkatzionis

“…Models trained on the 1000–2500 nm and 1400–2500 nm ranges showed minor reductions in accuracy, suggesting that classification is not solely driven by visible characteristics. …”
Get full text

Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease by Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Ta-Wei Chu, Dee Pei, Dee Pei

“…This study aimed to explore whether NAFLD could be effectively detected using 341 volatile organic compounds (VOCs) via 10 machine learning (Mach-L) algorithms in a cohort of 1,501 individuals.MethodsParticipants were selected from the Taiwan MJ cohort, which includes comprehensive demographic, biochemical, lifestyle, and VOCs data. …”
Get full text

First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole by The Event Horizon Telescope Collaboration, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Chi-kwan Chan, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Jason Dexter, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, José L. Gómez, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, Roman Gold, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Junhan Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Sera Markoff, Daniel P. Marrone, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Tomoaki Oyama, Feryal Özel, Daniel C. M. Palumbo, Nimesh Patel, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Paul Tiede, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Tyler Trent, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, Joseph R. Farah, Zheng Meyer-Zhao, Daniel Michalik, Andrew Nadolski, Hiroaki Nishioka, Nicolas Pradel, Rurik A. Primiani, Kamal Souccar, Laura Vertatschitsch, Paul Yamaguchi

“…We develop and fit geometric crescent models (asymmetric rings with interior brightness depressions) using two independent sampling algorithms that consider distinct representations of the visibility data. …”
Get full text

Machine learning identification of a novel vasculogenic mimicry-related signature and FOXM1’s role in promoting vasculogenic mimicry in clear cell renal cell carcinoma by Chao Xu, Sujing Zhang, Jingwei Lv, Yilong Cao, Yao Chen, Hao Sun, Shengtao Dai, Bowei Zhang, Meng Zhu, Yuepeng Liu, Junfei Gu

“…We developed a machine learning framework integrating 12 algorithms to establish a consistent VM-related signature (VRG_score). …”
Get full text

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network by Hui Zhou, Manmohan Kamboj, Yi Guo, Angela D Liese, Rebecca Anthopolos, Lu Zhang, John Chang, Anna Roberts, Tessa Crume, Brian E Dixon, Hui Shao, David C Lee, Lorna E Thorpe, Dimitri Christakis, Eneida A Mendonca, Katie Allen, Dana Dabelea, Giuseppina Imperatore, Mark Weiner, Meredith Akerman, Rong Wei, Kristi Reynolds, Annemarie G Hirsch, Jasmin Divers, Tianchen Lyu, Alex Ewing, Shaun Grannis, Yuan Luo, Bo Cai, Anthony Wong, Brian S Schwartz, Meda Pavkov, Meredith Lewis, Sarah Conderino, Jiang Bian, Yonghui Wu, Jihad S Obeid, Harold P Lehmann, Charles Bailey, Theresa Anderson, Elizabeth A Shenkman, Elizabeth Nauman, Christopher Forrest, Mattia Prosperi, Seho Park, Cara M Nordberg, Tessa L Crume, Anna Bellatorre, Stefanie Bendik, Marc Rosenman, Levon Utidjian, Mitch Maltenfort, Amy Shah, G Todd Alonso, Sara Deakyne-Davies, Tim Bunnell, Anne Kazak, Melody Kitzmiller, Daksha Ranade, Joseph J DeWalle, H Lester Kirchner, Dione G Mercer, Amy Poissant, Nimish Valvi, Jeff Warvel, Ashley Wiensch, Tamara Hannon, Eva Lustigova, Don McCarthy, Matthew T Mefford, George Lales, Allison Zelinski, Pedro Rivera, Thomas Carton, Victor W Zhong, Andrew Fair, Jessica Guillaume, Shahidul Islam, Alan Jacobson, Chinyere Okpara, Anand Rajan, Andrea Titus, Rebecca Conway, Toan Ong, Jack Pattee, Shawna Burgett, Bethlehem Shiferaw, Sarah J Bost, William T Donahoo, William R Hogan, Piaopiao Li, Lisa Knight, Caroline Rudisill, Jessica Stucker, Deborah Bowlby, Elaine Apperson, Deborah B Rolka

“…The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. …”
Get full text

Unveiling the pathogenic mechanisms of polyethylene terephthalate-microplastic-driven osteoarthritis and rheumatoid arthritis: PTGS2 signaling hub-oriented toxicity profiling by Jingkai Di, Shuang Wang, Lujia Liu, Keying Rong, Zijian Guo, Yingda Qin, Feida Wang, Chuan Xiang

“…Additionally, investigations into potential mechanisms were carried out through the utilization of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Furthermore, six algorithms such as Closeness and the ROC curve were used to further screen the target proteins with high correlation. …”
Get full text

Comparison of pulse pressure and stroke volume variations measured by three monitors in high-risk surgical patients by Barbora Cenková, Miloš Chobola, Vladimír Šrámek, Michal Šitina, Pavel Suk

“…Introduction: Dynamic indices of fluid responsiveness (FR) such as pulse pressure variation (PPV) and stroke volume variation (SVV) differ among hemodynamic monitors, which use proprietary algorithms, and vary even over a short period of time. …”
Get full text

Models of the Impact of Socio-Economic Shocks on Higher Education Development by Olena Rayevnyeva, Volodymyr Ponomarenko, Silvia Matusova, Kostyantyn Stryzhychenko, Stanislav Filip, Olha Brovko

“…The use of the developed models allows us to predict periods of shock points in the HES depending on shocks in the tendencies of GDP per capita and net migration.…”
Get full text

Diurnal distribution of phytoplankton in large shallow lakes based on time series clustering by Yanhong Chen, Haibin Cai, Yiqing Gong, Kun Lu, Jingqiao Mao, Weiyu Chen, Kang Wang, Huan Gao, Mingming Tian

“…This study demonstrates the potential of employing unsupervised clustering algorithms for identifying the diurnal dynamics of the phytoplankton distribution under complex influences, which can aid in optimizing the management and monitoring of shallow lakes.…”
Get full text

A Survey on the Deep Learning-Based Mismatch Removal: Principles and Methods by Shiyu Chen, Cailong Deng, Yong Zhang, Yong Wang, Qixin Zhang, Zhimin Zhou

“…Due to the inherent limitations of matching algorithms and the complexities associated with image contents, mismatches are inevitable and can have detrimental effects on downstream tasks in computer vision and remote sensing. …”
Get full text

Raman Spectra Classification of Pharmaceutical Compounds: A Benchmark of Machine Learning Models with SHAP-Based Explainability by Dimitris Kalatzis, Alkmini Nega, Yiannis Kiouvrekis

“…In addition to strong predictive performance, SHAP (SHapley Additive exPlanations) analysis was employed to interpret model decisions. …”
Get full text