Neutrophil extracellular traps-related genes contribute to sepsis-associated acute kidney injury by Tang Shaoqun, Yu Xi, Wang Wei, Luo Yaru, Lei Shaoqing, Qiu Zhen, Yang Yanlin, Sun Qian, Xia Zhongyuan

“…Differentially expressed genes were screened by “limma” package in R. Least absolute shrinkage and selection operator algorithm was applied to identify the hub genes. …”
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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

“…These person-centred approaches to T2DM management, which are more effective and personalized than some traditional strategies, only work because of the often-hidden synergies between AI algorithms in areas such as diagnostic criteria, predictive methods, and familiar classification tools for subgroups with relevant aspects/predictors on prognosis or treatment responsiveness.…”
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Novel exosome-associated LncRNA model predicts colorectal cancer prognosis and drug response by Chi Zhou, Qian Qiu, Xinyu Liu, Tiantian Zhang, Leilei Liang, Yihang Yuan, Yufo Chen, Weijie Sun

“…More importantly, we conducted an in-depth study on MIR4713HG, which may become an important therapeutic target in CRC.…”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…Exclusion criteria involved studies older than 20 years or lacking direct relevance. After screening 33 core articles and identifying 13 more through citation tracking, 46 articles were included in the final review.ResultsThis narrative review describes the characteristics of sedentary behavior, associated health risks, and the applications of ML in this context. …”
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A systematic review of neural network applications for groundwater level prediction by Samuel K. Afful, Cyril D. Boateng, Emmanuel Ahene, Jeffrey N. A. Aryee, David D. Wemegah, Solomon S. R. Gidigasu, Akyana Britwum, Marian A. Osei, Jesse Gilbert, Haoulata Touré, Vera Mensah

“…In conclusion, a hybrid metaheuristic algorithm produced more efficient results emphasizing their efficacy. …”
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Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease by Weizhe Zhen, Yu Wang, Hongjun Zhen, Weihe Zhang, Wen Shao, Yu Sun, Yanan Qiao, Shuhong Jia, Zhi Zhou, Yuye Wang, Leian Chen, Jiali Zhang, Dantao Peng, Dantao Peng

“…In the non-AD group, the trend of pathologic product levels with age was consistently opposite to that of the AD group. We finally screened the optimal AD diagnostic model (AUC=0.959) based on the results of correlation analysis and by using the Xgboost algorithm and SVM algorithm.ConclusionIn a novel finding, we observed that Tau protein and Aβ had opposite trends with age in both the AD and non-AD groups. …”
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ST-YOLO: a deep learning based intelligent identification model for salt tolerance of wild rice seedlings by Qiong Yao, Qiong Yao, Pan Pan, Pan Pan, Xiaoming Zheng, Xiaoming Zheng, Guomin Zhou, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Diversified feature extraction paths are introduced to enhance the ability of feature extraction; Introducing CAFM (Context Aware Feature Modulation) convolution and attention fusion modules into the backbone network to enhance feature representation capabilities while improving the fusion of features at various scales; Design a more flexible and effective spatial pyramid pooling layer using deformable convolution and spatial information enhancement modules to improve the model’s ability to represent target features and detection accuracy.ResultsThe experimental results show that the improved algorithm improves the average precision by 2.7% compared with the original network; the accuracy rate improves by 3.5%; and the recall rate improves by 4.9%.ConclusionThe experimental results show that the improved model significantly improves in precision compared with the current mainstream model, and the model evaluates the salt tolerance level of wild rice varieties, and screens out a total of 2 varieties that are extremely salt tolerant and 7 varieties that are salt tolerant, which meets the real-time requirements, and has a certain reference value for the practical application.…”
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A method for the identification of lactate metabolism-related prognostic biomarkers and its validations in non-small cell lung cancer by Weiyang Yang, Miao Gu, Yabin Zhang, Yunfan Zhang, Tao Liu, Di Wu, Juntao Deng, Min Liu, Youwei Zhang

“…We proposed a Cox elastic-net regression combined with genetic algorithm (GA-EnCox) to predict prognosis and optimize the selection of key biomarkers. …”
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Real-World Parkinson’s Hand Tremor Detection Using Ensemble Learning Techniques by Sungwook Hur, Jieming Zhang, Moon-Hyun Kim, Tai-Myoung Chung

“…Our method first applies a dynamic scanning mechanism to screen out valid walking fragments from whole walking sequence. …”
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Hybrid closed-loop systems for managing blood glucose levels in type 1 diabetes: a systematic review and economic modelling by Asra Asgharzadeh, Mubarak Patel, Martin Connock, Sara Damery, Iman Ghosh, Mary Jordan, Karoline Freeman, Anna Brown, Rachel Court, Sharin Baldwin, Fatai Ogunlayi, Chris Stinton, Ewen Cummins, Lena Al-Khudairy

“…The system includes a combination of real-time continuous glucose monitoring from a continuous glucose monitoring device and a control algorithm to direct insulin delivery through an insulin pump. …”
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Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…Abstract This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. …”
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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

“…A total of 5 machine learning algorithms, namely random forest, Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting, Gradient Boosting Machine, and CatBoost were used. …”
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Poor Nutritional Status Increases Risk of Postoperative Adverse Events after Surgical Management of Traumatic Ankle Fracture by Sanket Mehta MD, Nicholas Danford MD

“…Patients with poor nutritional status were older (56 vs. 51 years), more likely to present in shock (7.5% vs. 2.3%) and due to motor vehicle collision mechanism (all P< 0.001). …”
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Helicobacter pylori eradication treatment for gastric carcinoma prevention in asymptomatic or dyspeptic adults: systematic review and Bayesian meta-analysis of randomised controlle... by Teruhiko Terasawa, Isao Miyashiro, Katsuaki Kato, Takaki Yoshikawa, Reo Takaku, Hiroshi Nishida

“…However, concerns about supporting unfocused screening and eradication programme in healthy, asymptomatic populations have arisen. …”
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The clinical utility and safety of biomarker-guided immunosuppression withdrawal in liver transplantation: the LIFT prospective RCT by Julien Vionnet, Rosa Miquel, Juan G Abraldes, Juan-Jose Lozano, Pablo Ruiz, Miquel Navasa, Aileen Marshall, Frederik Nevens, William Gelson, Joanna Leithead, Steven Masson, Elmar Jaeckel, Richard Taubert, Phaedra Tachtatzis, Dennis Eurich, Kenneth Simpson, Eliano Bonaccorsi-Riani, James Ferguson, Alberto Quaglia, Maria Elstad, Marc Delord, Abdel Douiri, Alberto Sánchez-Fueyo

“…This was done by enrolling patients more than 3 years after transplantation and allocating them at random to two groups. …”
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STOP-BANG: a Mandatory Tool for Targeted Respiratory Therapy in Bariatric Patients by R. D. Skvortsova, K. А. Аnisimova, K. А. Popova, V. А. Pavlova, А. N. Kulikov, D. I. Vasilevsky, S. G. Balandov, Z. А. Zaripova, А. А. Kazachenko, Yu. D. Rabik, T. S. Razumovskaya

“…Identification of patients with obstructive sleep apnea syndrome and high respiratory risk, optimization of the screening algorithm for these patients and administration of preventive non-invasive lung ventilation, makes it possible to prevent the development of perioperative complications, reduce duration of hospital stay and reduce mortality in patients undergoing surgery and bariatric surgery specifically.The objective: to evaluate the effectiveness of STOP-BANG questionnaire for preventive targeted respiratory therapy to reduce the risk of complications in bariatric patients. …”
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Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

“…ObjectiveTo address the challenge of accurately capturing weak features in vibration signals under strong noise interference, a joint filtering method combining ensemble empirical mode decomposition (EEMD), fast kurtogram (FK), and adaptive maximum correlation kurtosis deconvolution (AMCKD) was proposed.MethodsFirstly, the vibration signal was decomposed into multiple intrinsic mode functions (IMF) via EEMD for multiscale analysis. …”
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Diagnostic Value of F-FDG PET/CT Radiomics in Lymphoma: A Systematic Review and Meta-Analysis by Chaoying Liu MD, Jun Zhao PhD, Heng Zhang PhD, Xinye Ni PhD

“…Six meta-regressions were conducted on study performance, considering sample size, image modality, region of interest (ROI) selection, ROI segmentation, radiomics mode, and algorithms. Results In total, 20 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement were included for this systematic review and meta-analysis. …”
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Anti-EBV: Artificial intelligence driven predictive modeling for repurposing drugs as potential antivirals against Epstein-Barr virus by Hiteshi Vaidya, Sakshi Gautam, Manoj Kumar

“…The top-performing model was used to screen approved drugs from DrugBank, identifying potential repurposed drugs namely arzoxifene, succimer, abemaciclib and many more. …”
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Visual impairments associated with the treatment of malignant tumors of the female reproductive system: a literature review and practical recommendations for oncogynecologists by Y. A. Chuikova, O. A. Odintsova, D. V. Skalozub, A. G. Antonyuk, A. A. Kabartai, A. N. Nurmamatova, R. M. Azimov, P. A. Snatenkova, A. A. Silantyev, S. R. Osina, D. S. Minasyan, S. A. Lashevich, I. A. Isaeva, E. A. Rukhlyadyeva

“…Practical recommendations are provided for screening, monitoring, and managing patients at risk of ocular complications, including referral algorithms and treatment modification strategies. …”
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