Secure Lattice-Based Signature Scheme for Internet of Things Applications by Sunil Prajapat, Deepika Gautam, Pankaj Kumar, Srinivas Jangirala, Ashok Kumar Das, Biplab Sikdar

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Towards accurate L4 ocean colour products: Interpolating remote sensing reflectance via DINEOF by Christian Marchese, Simone Colella, Vittorio Ernesto Brando, Maria Laura Zoffoli, Gianluca Volpe

“…Ocean colour (OC) remote sensing benefits society by providing continuous biological and ecological parameters relevant to sustainable marine resource exploitation. …”
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SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

“…Currently, none of the presented algorithms can meet the criteria of economic efficiency, even in the most developed countries. …”
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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer by Erha Munai, Siwei Zeng, Ze Yuan, Dingyi Yang, Yong Jiang, Qiang Wang, Yongzhong Wu, Yunyun Zhang, Dan Tao

“…Four different machine learning (ML) algorithms were used to create prediction models for BMs in ES-SCLC patients. …”
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Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma by Zhen Chen, Yongjun Zhang

“…The sequencing data of immune-related genes were comprehensively analyzed by introducing a new computational framework and 10 machine learning algorithms (a total of 101 combinations) to determine the prognostic genes, which were further combined to develop an immune prognostic signature (IMMPS) using the stepCox and Ridge methods. …”
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Named Entity Recognition in Aviation Products Domain Based on BERT by Mingye Yang, Bernadin Namoano, Maryam Farsi, John Ahmet Erkoyuncu

“…The first step of this method is to establish an ontology model of aviation products and annotate the relevant text data to form a dataset for training the named entity model. …”
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Association between different insulin resistance surrogates and erectile dysfunction in non-diabetic men: a large population-based study by Shenghao Wu, Weiting Xia

“…When segmenting effects were detected, recursive algorithms were used to determine potential inflection points. …”
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AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta) by Annemiek Maaskant, Donghyeok Lee, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A. M. Langermans, Evgeni Levin

“…Conclusion Our approach demonstrated the ability to predict a wide range of clinically relevant microbial genera and microbial groups in the gut microbiome based on digital images from a fecal smear. …”
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Unstructured Electronic Health Records of Dysphagic Patients Analyzed by Large Language Models by Luisa Neubig, Deirdre Larsen, Melda Kunduk, Andreas M. Kist

“…We utilize clustering algorithms on the extracted diagnostic features to identify distinct groups of patients who share similar pathophysiological swallowing dysfunctions.Results: We found that basic NLP techniques often provide limited insights due to the high variability of the data. …”
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MANAGEMENT AND ORGANIZATIONAL AND ECONOMIC CONDITIONS OF STRENGTHENING THE MARKETING ACTIVITY OF THE ENTERPRISE AND MAINTAINING EFFICIENT AGRO BUSINESS by L. Lomovskykh, M. Ponomarova, L. Chip, E. Krivosheya, O. Lisova

“…To strengthen marketing activities and conduct effective agribusiness, algorithms have been developed to gain a competitive advantage. …”
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Efficient evidence selection for systematic reviews in traditional Chinese medicine by Yizhen Li, Zhe Huang, Zhongzhi Luan, Shujing Xu, Yunan Zhang, Lin Wu, Darong Wu, Dongran Han, Yixing Liu

“…Methods We integrated an established deep learning model (Evi-BERT combined rule-based method) with Boolean logic algorithms and an expanded retrieval strategy to automatically and accurately select potential evidence with minimal human intervention. …”
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Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline by HongYi Li, Jun-Fen Fu, Andre Python

“…With the rapid development of LLMs, clinicians face a growing challenge in determining the most suitable algorithms to support their work. ObjectiveWe aimed to provide clinicians and other health care practitioners with systematic guidance in selecting an LLM that is relevant and appropriate to their needs and facilitate the integration process of LLMs in health care. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

“…Furthermore, machine learning algorithms can be employed to analyze complex datasets, enhancing our ability to predict the impacts of MPs on plant health and crop performance under different environmental conditions. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. The real challenge is not just about embracing AI’s benefits but ensuring it is used responsibly, fairly, and in a way that aligns with educational values. …”
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Using large language models for enhanced fraud analysis and detection in blockchain based health insurance claims by Ruba Islayem, Senay Gebreab, Walaa AlKhader, Ahmad Musamih, Khaled Salah, Raja Jayaraman, Muhammad Khurram Khan

“…The architecture, sequence diagrams, and implementation algorithms outline the development process, while testing scenarios demonstrate the system’s ability to detect fraud such as inflated costs, unnecessary treatments, and unrendered services. …”
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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

“…Two machine-learning algorithms, i.e., random forest classifier (RFC) and gradient boosting classifier, were trained on the entire national-scale dataset and subsequently applied to assess their performance in predicting habitat types in the Saronikos Gulf (regional scale) using various environmental factors as predictors. …”
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MORPHOLOGICAL VARIABILITY OF LEAVES OF ACER NEGUNDO L. POPULATIONS IN THE ALTITUDINAL GRADIENT OF THE NORTH-WEST CAUCASUS (REPUBLIC OF ADYGEA) by Evgenia M. Ednich, Irina V. Chernyavskaya, Tatyana N. Tolstikova, Mariet N. Khagur, Marat V. Aliev

“…Understanding the adaptive strategies of invasive species, including Аcer negundo L. based on morphological mechanisms of adaptation in the altitude gradient is relevant for predicting of A. negundo behavior in the floodplain forests of Adygea and will be a basis for further study of A. negundo invasiveness in the North-West Caucasus. …”
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A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting by Pan Wu, Zilin Huang, Yuzhuang Pian, Lunhui Xu, Jinlong Li, Kaixun Chen

“…Results show that the proposed method outperforms other deep learning algorithms (such as recurrent neural network (RNN) and convolutional neural network (CNN)) in terms of both calculating efficiency and prediction accuracy. …”
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AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis by Hind M. AlOsaimi, Aseel M. Alshilash, Layan K. Al-Saif, Jannat M. Bosbait, Roaa S. Albeladi, Dalal R. Almutairi, Alwaleed A. Alhazzaa, Tariq A. Alluqmani, Saud M. Al Qahtani, Sara A. Almohammadi, Razan A. Alamri, Abdullah A. Alkurdi, Waleed K. Aljohani, Raghad H. Alraddadi, Mohammed K. Alshammari

“…AI models, particularly deep learning and machine learning algorithms demonstrated high accuracy in predicting biomarker status. …”
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Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…The goal is to identify critical points in implantation to improve therapies.MethodsA comprehensive literature search identified 1474 relevant papers, 11 of which met the inclusion criteria. …”
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