AIF: Infrared and Visible Image Fusion Based on Ascending–Descending Mechanism and Illumination Perception Subnetwork by Ying Liu, Xinyue Mi, Zhaofu Liu, Yu Yao

“…However, the existing image fusion algorithms rarely consider light factor in the modeling process. …”
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Artificial Intelligence in Advancing Algal Bioactive Ingredients: Production, Characterization, and Application by Bingbing Guo, Xingyu Lu, Xiaoyu Jiang, Xiao-Li Shen, Zihao Wei, Yifeng Zhang

“…This review examines the multidimensional mechanisms by which AI enables and optimizes these processes: (1) AI-powered predictive models, integrated with machine learning algorithms (MLAs), Industry 4.0, and other advanced digital systems, support real-time monitoring and control of intelligent bioreactors, allowing for accurate forecasting of cultivation yields and market demand. (2) AI facilitates in-depth analysis of gene regulatory networks and key metabolic pathways, enabling precise control over the biosynthesis of targeted compounds. (3) AI-based spectral imaging and image recognition techniques enable rapid and reliable identification, classification, and quality assessment of active components. (4) AI accelerates the transition from mass production to the development of personalized medical and functional nutritional products. …”
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Integrating machine learning and reliability analysis: A novel approach to predicting heavy metal removal efficiency using biochar by Mohammad Sadegh Barkhordari, Chongchong Qi

“…This research introduces an advanced machine learning (ML) framework, utilizing deep forest (DF) algorithms, to predict and optimize the efficiency HM removal through biochar applications. …”
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Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules. by Xiaolin Xiao, Aida Moreno-Moral, Maxime Rotival, Leonardo Bottolo, Enrico Petretto

“…Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. …”
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Personalizing mHealth Interventions for Occupational Stress: Protocol for a Randomized Pilot Study by Beatrix Kunas, Oliver Jung, Christoph Schranz, Mathias Schmoigl-Tonis, Manuela Ploessnig, Anton-Rupert Laireiter

“…The app offered interventions based on algorithms, which altered the probability of their selection after learning from the data, thereby personalizing the user experience. …”
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Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…These findings highlight the potential of TinyML to provide accessible, reliable, and real-time diagnostic tools, particularly in remote and underserved areas, demonstrating the transformative impact of integrating advanced AI algorithms into portable medical devices. This advancement facilitates the prospect of automated respiratory health screening using lung sounds.…”
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Metabolic profile changes in patients with rheumatoid arthritis detected using mass spectrometry by Xue Wu, Qi Yang, Shanshan Liu, Peng Yang, Zhengqi Liu, Zhitu Zhu

“…Methods A total of 533 participants, including 382 healthy individuals and 151 RA patients, were recruited to explore altered metabolic profiles through the analysis of dried blood spot samples by mass spectrometry. Multiple algorithms were applied to identify potential biomarkers. …”
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The class project of cyber-driver by P. S. Sorokoumov

“…In robotic perception models the situation is similar: casual human tasks as image recognition or scene analysis need complex algorithms and huge computer resources if performed by robots. …”
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From gene expression to causal associations: investigating the role of ferroptosis in cataract development by Chen Li, Xian-bing Yuan, Yi-cheng Lu, Zi-yue Song

“…Nine hub genes were identified using the PPI network and five algorithms in Cytoscape. The RT-PCR results validated TIGAR, IL6, ATF3, and TNFAIP3 as potential biomarkers. …”
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Performance Assessment of Undifferenced GPS/Galileo Precise Time Transfer with a Refined Clock Model by Wei Xu, Pengfei Zhang, Lei Wang, Chao Yan, Jian Chen

“…Conventional Global Navigation Satellite System (GNSS) time transfer algorithms typically model receiver clock offsets as white noise for estimation, neglecting the physical characteristics of atomic clocks, which consequently limits the performance of GNSS time transfer. …”
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Flow Field Analysis and Development of a Prediction Model Based on Deep Learning by Yingjie Yu, Xiufeng Zhang, Lucai Wang, Rui Tian, Xiaobin Qian, Dongdong Guo, Yanwei Liu

“…The proposed model was validated by comparing its predictions with those predicted by the MIKE21 flow model of the ocean area within proximity to Dalian Port (which used a commercial numerical model), as well as those predicted by other deep learning algorithms. The results showed that the model offers significant advantages and efficiency in simulating and predicting ocean surface currents. …”
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Reconstruction of Tokamak Plasma Emissivity Distribution by Approximation with Basis Functions by Tomasz Czarski, Maryna Chernyshova, Katarzyna Mikszuta-Michalik, Karol Malinowski

“…This contribution presents the development of numerical algorithms addressing the problem of radiation tomography reconstruction. …”
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Prognostic tools or clinical predictions: Which are better in palliative care? by P Stone, V Vickerstaff, A Kalpakidou, C Todd, J Griffiths, V Keeley, K Spencer, P Buckle, D Finlay, R Z Omar

“…<h4>Conclusions</h4>Although four commonly used prognostic algorithms for palliative care generally showed good discrimination and calibration, none of them demonstrated superiority to CPS. …”
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SIGNAL MODEL FOR SPATIAL POSITION SENSORS IN MAGNETIC TRACKING SYSTEMS by Roman Holyaka, Tetyana Marusenkova, Dmytro Fedasyuk

“…Further development of the presented results implies the proposed signal model to be used when solving problems of developing and specifying algorithms of spatial position calculation, system debugging and rapid analysis, optimization of calibration procedures.…”
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Review of open libraries for pharmacoeconomic analysis in R environment by I. A. Lackman, R. I. Sladkov, V. M. Timiryanova

“…The selected libraries can be divided into three classes: packages for calculating various quality of life indices, libraries for calculating indicators and indices of economic effectiveness of medical interventions (DALY, QALY, ICER), libraries for performing sensitivity analysis of the effect of medical interventions based on decision tree algorithms and Markov models. The libraries “heemod”, “hesim”, “rdesign” allow building simple Markov and semi-Markov models, but preference should be given to “heemod” due to the presence of vignettes. …”
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Using weak signals to predict spontaneous breathing trial success: a machine learning approach by Romain Lombardi, Mathieu Jozwiak, Jean Dellamonica, Claude Pasquier

“…The study focuses on the development of ML algorithms to predict the success of the spontaneous breathing trial based on a combination of discrete variables and biosignals (time series) recorded during the 24 h prior to the SBT. …”
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Current Evidence Supporting the Role of miRNA as a Biomarker for Lung Cancer Diagnosis Through Exhaled Breath Condensate Collection: A Narrative Review by Paolo Albino Ferrari, Cosimo Bruno Salis, Antonio Macciò

“…Large-scale, multicenter validation studies are needed to establish robust diagnostic algorithms integrating EBC-derived miRNAs with existing clinical tools. …”
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Generative AI on professional development: a narrative inquiry using TPACK framework by Buddhi Laxmi Lakhe Shrestha, Niroj Dahal, Md. Kamrul Hasan, Santosh Paudel, Hiralal Kapar

“…The study emphasizes the need to balance GenAI's technological benefits with human-centric pedagogy, underlining the importance of ethical guidelines, institutional training, and collaborative peer learning to reduce the dependency and algorithmic biases by aligning GenAI integration with TPACK principles—harmonizing technological, pedagogical, and content knowledge—the research advocates for structured support systems to empower educators in using AI responsibly. …”
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Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews by Kristen Foley, Caitlan McLean, Reece De Zylva, Gregorius Asa, Jordana Maio, Samantha Batchelor, Gideon Dzando, Ahmad Dimassi

“…Beyond only literature retrieval, some AI tools describe their use-value as being able to appraise and synthesise contrasting evidence within and across papers; work like ‘Spotify’ to cultivate a personalised ecosystem of research articles that evolves via algorithmic learning; and suggest new directions for research based on existing evidence about a topic and an assessment of knowledge gaps. …”
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High-content screening (HCS) workflows for FAIR image data management with OMERO by Riccardo Massei, Wibke Busch, Beatriz Serrano-Solano, Matthias Bernt, Stefan Scholz, Elena K. Nicolay, Hannes Bohring, Jan Bumberger

“…Furthermore, we suggest future research direction, including developing new workflows and integrating machine learning algorithms for automated image analysis. This study provides a blueprint for developing efficient and effective image data management systems for HCS experiments and demonstrates how different WMS approaches can be applied to create reusable, semi-automated workflows for HCS bioimaging data management using OMERO.…”
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