Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…The model's performance was evaluated in a cloud-based environment using two datasets: ORIGA and G1020. …”
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High prevalence of resistance to macrolides and fluoroquinolones in Mycoplasma genitalium isolated from patients in two Russian megalopolises – Moscow and St. Petersburg in 2021– 2... by Edelstein I.A., Gushchin A.E., Gladin D.P., Romanov A.V., Negasheva E.S., Frigo N.V., Kozlov R.S., Potekaev N.N., Kozlova N.S., Borukhovich D.G.

“…The most common combination of mutations was A2059G (23S rRNA) + S80I (parC), which made up to 33% (18/54) in St. Petersburg and 25.7% (25/97) in Moscow. …”
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3D Film Animation Image Acquisition and Feature Processing Based on the Latest Virtual Reconstruction Technology by Siwei Wu, Shan Xiao, Yihua Di, Cheng Di

“…Finally, the target 3D face is reconstructed using the feature points of the target face for model matching. The experimental results show that the algorithm reconstructs faces with high realism and accuracy, and the algorithm can reconstruct expression faces.…”
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Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+) by Julia Treml, Viktoria Schmidt, Elmar Braehler, Matthias Morfeld, Anette Kersting

“…Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. …”
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Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study by Ting Peng, Rujia Miao, Hao Xiong, Yanhui Lin, Duzhen Fan, Jiayi Ren, Jiangang Wang, Yuan Li, Jianwen Chen

“…In the test group, all AUC were also greater than 0.80. The LightGBM model showed the best IR prediction performance with an accuracy of 0.7542, sensitivity of 0.6639, specificity of 0.7642, F1 ConclusionBy leveraging low-cost laboratory indicators and questionnaire data, the LightGBM model effectively predicts IR status in nondiabetic individuals, aiding in large-scale IR screening and diabetes prevention, and it may potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.…”
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Evaluating the role of insulin resistance in chronic intestinal health issues: NHANES study findings by Dongyao Zhao, Meihua Zhao, Bing Gao, He Lu

“…Key variables were selected via the Boruta algorithm and incorporated into weighted multivariate logistic regression models. …”
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LABORATORY OF CLINICAL IMMUNOLOGY N.V. SKLIFOSOVSKY RESEARCH INSTITUTE FOR EMERGENCY MEDICINE (HISTORY AND PRESENT) by M. A. Godkov, G. V. Bulava

“…During 45 years of work of immunological service formed the algorithm of the adequate immunological screening was formed, number of innovative methods of diagnosis was developed, the ideology of post-test counseling of patients by immunologists was created, mathematical methods of storage, modeling and processing of research results was introduced. …”
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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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Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches by Hu J, Chen Z, Wang J, Xu A, Sun J, Xiao W, Yang M

“…Subsequently, neuroinflammation-related genes were obtained to construct a neuroinflammation-related signature. The AddModuleScore algorithm was used to calculate neuroinflammation scores for each cell subpopulation, whereas the CellCall algorithm was used to assess the crosstalk between neutrophils and other cell subpopulations. …”
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A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network by Owen He, Daoxing Chen, Yimei Li

“…In independent test sets, ReproTox-CMPNN achieved a mean AUC of 0.946, ACC of 0.857 and F1 score of 0.846, surpassing traditional algorithms to establish itself as a new state-of-the-art model in this field. …”
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Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in cancer cells... by Yifan Xu, Chonghui Zhang, Jinpeng Wu, Pin Guo, Nan Jiang, Chao Wang, Yugong Feng

“…Notably, the expression levels of these three hub genes and the lactylation level of TUBB2A in GBM tissues were significantly higher compared to those in normal tissues.ConclusionsWe propose and validate a IQR lactylation screening method that provides potential insights for GBM therapy and an effective framework for developing gene screening models applicable to other diseases and pathogenic mechanisms.…”
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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…An Enhanced Particle Swarm Optimization (EPSO) algorithm is integrated to automatically fine-tune CNN hyperparameters, thereby minimizing manual effort and enhancing computational efficiency. …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

“…Advanced machine learning (ML) and deep learning (DL) methods have recently been utilized in Drug Response Prediction (DRP), and these models use the details from genomic profiles, such as extensive drug screening data and cell line data, to predict the response of drugs. …”
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Research and application of image recognition-based identification for flesh browning of loquat fruits by CHEN Yujia, DENG Chaojun, ZHANG Tingting, WANG Xiuping, CHEN Xiuping, ZHAO Jianing, MA Cuilan, JIANG Jimou

“…The Euclidean distance algorithm indicated that the percentage of browning area in the white flesh type was significantly higher than that in the red flesh type. …”
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Prevalence, types, risk factors and clinical correlates of anaemia in older people in a rural Ugandan population. by Joseph O Mugisha, Kathy Baisley, Gershim Asiki, Janet Seeley, Hannah Kuper

“…Clinicians should consider screening older people with HIV or malaria for anaemia. …”
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High-throughput discovery of genetic determinants of circadian misalignment. by Tao Zhang, Pancheng Xie, Yingying Dong, Zhiwei Liu, Fei Zhou, Dejing Pan, Zhengyun Huang, Qiaocheng Zhai, Yue Gu, Qingyu Wu, Nobuhiko Tanaka, Yuichi Obata, Allan Bradley, Christopher J Lelliott, Sanger Institute Mouse Genetics Project, Lauryl M J Nutter, Colin McKerlie, Ann M Flenniken, Marie-France Champy, Tania Sorg, Yann Herault, Martin Hrabe De Angelis, Valerie Gailus Durner, Ann-Marie Mallon, Steve D M Brown, Terry Meehan, Helen E Parkinson, Damian Smedley, K C Kent Lloyd, Jun Yan, Xiang Gao, Je Kyung Seong, Chi-Kuang Leo Wang, Radislav Sedlacek, Yi Liu, Jan Rozman, Ling Yang, Ying Xu

“…We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. …”
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Atrial fibrillation with thrombotic complications. Justification of the diagnosis and treatment regimen according to evidence-based medicine (clinical case) by L.O. Martymianova, E.P. Kamenska, A.O. Bulyha, K.О. Serdyuk

“…Diagnosis and systematic screening of AF, as well as timely assessment of stroke risk, are of paramount importance for the prognosis of patients, especially in older age groups. …”
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Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network by Gang Zhao, Changyu Han, Zhongxiang Yu, Zhipan Li, Guoao Yu, Hongmei Zhang, Dadong Zhao, Zhengyi Jiang

“…The single-stage object detection algorithm YOLOv5 (You Only Look Once) based on convolutional neural network model calculation is used, the scale detection layer and positioning loss function of the YOLOv5 algorithm are improved and optimized, and the improved YOLOv5 algorithm is used for experiments. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In medical imaging, deep learning algorithms, especially those trained with genetic algorithms, have demonstrated immense promise to improve the accuracy of pneumonia and COVID-19 diagnosis from chest X-rays. …”
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Research Progress and Prospect of Green Infrastructure with Public Health Promotion Function by Tongyu LI, Junyi LIXU, Binxia XUE, Yan (USA) SONG

“…To manage the multidimensionality of GI research, cluster analysis is performed using a Word2Vec model combined with a K-means algorithm to integrate different GI forms into a coherent classification system.ResultsThe results show that GI can be clearly divided into different categories, such as urban green spaces and parks, high-interaction spaces, trees in built-up areas, water management and biofiltration systems, community and residential greening, green roofs and facades, linear green networks, and broader macro-GI strategies. …”
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