Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

“…Receiver operating characteristic (ROC) curve analyses assessed method agreement across different patient subpopulations. Predictive values were calculated for the total population and the ten different subpopulations at different cut-offs. …”
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Electronic nose and machine learning for modern meat inspection by Ivan Shtepliuk, Guillem Domènech-Gil, Viktor Almqvist, Arja Helena Kautto, Ivar Vågsholm, Sofia Boqvist, Jens Eriksson, Donatella Puglisi

“…The model demonstrated robust predictive performance with a Kappa value of approximately 0.926, indicating near-perfect agreement between the predictions and actual classifications. …”
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Identification and functional analysis of energy metabolism and pyroptosis-related genes in diabetic nephropathy by Shan He, Jian Ye, Yu Wang, Lu yang Xie, Si Yi Liu, Qin kai Chen

“…PPI network analysis highlighted the central role of these genes within the relevant pathways. Predictive modeling demonstrated interactions between EMAPRDEGs, 69 miRNAs, and 117 TFs. …”
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Significance of Immune-Related Genes in the Diagnosis and Classification of Intervertebral Disc Degeneration by Bo Wu, Xinzhou Huang, Mu Zhang, Wei Chu

“…Then, we utilized a random forest (RF) model to screen six candidate IRGs to predict the risk of IDD. A nomogram was developed on the basis of six candidate IRGs, and DCA showed that patients could benefit from the nomogram. …”
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Co‐Expression of MHC‐II and ANXA1: Mediators of PD‐1/PD‐L1 Therapy Resistance in Breast Cancer by Hao Wang, Ji‐Feng Sun, Chen Wang, Zhan‐Sheng Jiang, Zhong‐Sheng Tong

“…ANXA1 could serve as both a predictive marker for treatment resistance and a therapeutic target to enhance the efficacy of immunotherapy.…”
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Global change drives potential niche contraction and range shift of globally threatened African vulture by Gemechis B. Mosisa, Nega Tassie, Fatuma Yesuf

“…All considered Species distribution models (SDMs) achieved high predictive performance, with AUC-ROC values exceeding 0.9.The model predicted a total of approximately 19,453 ha of suitable habitat for Ruppell's vultures in Africa, with East Africa identified as the most prominent region under the current climate scenario. …”
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Experimental and computational evaluation of knee implant wear and creep under in vivo and ISO boundary conditions by Michael J. Dreyer, Seyyed Hamed Hosseini Nasab, Philippe Favre, Fabian Amstad, Rowena Crockett, William R. Taylor, Bernhard Weisse

“…Future work should focus on expanding the range of daily activities simulated and addressing model sensitivity to contact mechanics to further enhance predictive accuracy.…”
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Pathogen-specific epitopes as epidemiological tools for defining the magnitude of Mycobacterium leprae transmission in areas endemic for leprosy. by Marcia V S B Martins, Marjorie M da S Guimarães, John S Spencer, Mariana A V B Hacker, Luciana S Costa, Fernanda M Carvalho, Annemieke Geluk, Jolien J van der Ploeg-van Schip, Maria A A Pontes, Heitor S Gonçalves, Janvier P de Morais, Tereza J P G Bandeira, Maria C V Pessolani, Patrick J Brennan, Geraldo M B Pereira

“…The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a new tool for predicting the magnitude of M. leprae transmission in a given population.…”
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Real-Time Caterpillar Detection and Tracking in Orchard Using YOLO-NAS Plus SORT by Sumesh Nair, Guo-Fong Hong, Chia-Wei Hsu, Chun-Yu Lin, Shean-Jen Chen

“…With an inference time of just 0.2 milliseconds, SORT enabled real-time tracking and accurately predicted caterpillar positions under wind interference, further improving reliability. …”
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Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures by Timo F.W. Soeterik, Xiaobo Wu, Roderick C.N. Van den Bergh, Claudia Kesch, Fabio Zattoni, Ugo Falagario, Alberto Martini, Marcin Miszczyk, Vittorio Fasulo, Martina Maggi, Veeru Kasivisvanathan, Pawel Rajwa, Giancarlo Marra, Giorgio Gandaglia, Peter K.F. Chiu

“…PSMA PET has emerging potential to improve csPCa prediction in combination with MRI and may further reduce unnecessary biopsies. …”
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Human-in-the-Loop Optimization of the Stiffness and Alignment of a Prosthetic Foot to Reduce the Metabolic Cost of Walking by Thijs Tankink, Han Houdijk, Johnnidel Tabucol, Marco Leopaldi, Juha M. Hijmans, Raffaella Carloni

“…Walking on the prosthetic foot with optimized settings during the post-test resulted in a significant reduction in metabolic cost compared to the pre-test with standard settings (−10.6%). …”
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AI-based classification of anticancer drugs reveals nucleolar condensation as a predictor of immunogenicity by Giulia Cerrato, Peng Liu, Liwei Zhao, Adriana Petrazzuolo, Juliette Humeau, Sophie Theresa Schmid, Mahmoud Abdellatif, Allan Sauvat, Guido Kroemer

“…Conclusions We developed AI-based algorithms for predicting CON-inducing drugs based on molecular descriptors and their validation using automated micrographs analysis, offering a new approach for screening ICD inducers with minimized adverse effects in cancer therapy.…”
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Identification of RNA Modification-Associated Alternative Splicing Signature as an Independent Factor in Head and Neck Squamous Cell Carcinoma by Jie Liu, Wenmin Deng, Zhiwen Xiao, Xiaofeng Huang, Minmin Lin, Zhen Long

“…Besides, a nomogram prediction model of quantitative prognosis has also been developed, which has robust effectiveness in predicting prognosis. …”
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Toward Intelligent Financial Advisors for Identifying Potential Clients: A Multitask Perspective by Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

“…Thus, extracting useful information from various characteristics of users and further predicting their purchase inclination are urgent. However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. …”
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Use of electrochemical energy storage systems in autonomous power supply systems to reduce fuel consumption of power installations by A. I. Fedotov, E. A. Fedotov, A. F. Abdullazyanov

“…In the context of predicted changes in power profiles (work / weekend days), optimal control scenarios are calculated individually. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The methodology is strategically designed to address the complexities and variations in cephalometric images through a dual learning process: building base learners using end-to-end regression approaches and then constructing a meta-learner that ensembles the output of the base models to obtain collective predictions. Two primary approaches are followed to design base learners: an end-to-end single model and a multi-model strategy for localizing landmarks. …”
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The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

“…Ridge regression was used in combination with an algorithm for sequential reduction of attribute space.Results. …”
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Multi-fidelity modelling of a high bypass ratio turbofan engine with variable area nozzle by Andrea Magrini, Ernesto Benini

“…Low-speed mission points are confirmed to be those that benefit the most from an enlarged fan nozzle area, with a possible improvement of 3% in terms of thrust and specific fuel consumption at take-off and approach using a 10% larger area, similarly predicted by both 2D and 3D models. A preliminary acoustic evaluation based on semi-empirical noise models indicates a modest effect on noise emissions, with up to 1 dB reduction in microphone signature at the sideline for a nozzle area increased by 10%.…”
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A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery by Abdul Gani Abdul Jameel

“…AI-based blending systems are more flexible and will enable the refineries to meet the product specifications regularly and result in cost reduction owing to the fall in quality giveaways. The AI-powered process discussed can predict, with much better accuracy, critical combustion properties of gasoline such as the Research Octane Number (RON), Motor Octane Number (MON), and Antiknock Index (AKI), compared to the classical LP models, with the added advantage of optimization of the blend ratio in real time. …”
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Multi-objective optimization of residential energy-saving design based on fuzzy multi-criteria decision-making behavior model by Suzhen Pei, Gaoxiang Chen, Jian Yao, Yichen Dang

“…Traditional building energy simulation models often neglect the stochastic nature of occupant behavior and multi-device interaction, leading to discrepancies between predicted and actual energy consumption. This study introduces a multi-objective optimization framework based on a Fuzzy Multi-Criteria Decision-Making (FMCDM) behavioral model. …”
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