Extracellular mRNA detected by molecular beacons in tethered lipoplex nanoparticles for diagnosis of human hepatocellular carcinoma. by Xinmei Wang, Kwang Joo Kwak, Zhaogang Yang, Aili Zhang, Xiaoli Zhang, Rachael Sullivan, Dan Lin, Robert L Lee, Carlos Castro, Kalpana Ghoshal, Carl Schmidt, L James Lee

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Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit by Mengke Ma, Jiatong Liu, Caiyun Li, Yingxue Chen, Huishu Jia, Aijie Hou, Hongzeng Xu

“…The least absolute shrinkage selection operator (LASSO) regularization algorithm and the extreme gradient boosting (XGBoost) for feature importance evaluation were used to screen important predictors. …”
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Exploration of the Prognostic Markers of Multiple Myeloma Based on Cuproptosis‐Related Genes by Xiao‐Han Gao, Jun Yuan, Xiao‐Xia Zhang, Rui‐Cang Wang, Jie Yang, Yan Li, Jie Li

“…Additionally, key module genes were identified through weighted gene co‐expression network analysis. A univariate Cox algorithm and multivariate Cox analysis were employed to obtain biomarkers of MM and build a prognostic model before conducting independent prognostic analysis. …”
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Exploring the role of hepsin in prostate cancer: bioinformatics, molecular Docking and molecular dynamics simulations by Hongying Peng, Dan Du, Zhonggui Hu, Zhiliang Xia

“…Although significant advances have been made in early detection, therapeutic strategies for advanced and metastatic PCa remain limited. …”
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An integrated bioinformatic investigation of succinic acid metabolism related genes in ccRCC followed by preliminary validation of SLC25A4 in tumorigenesis by Dong Yue, Fengyun Dong, Sen Wang, Miao Zheng

“…The univariate Cox algorithm, LASSO, and multivariate Cox analysis were performed to obtain biomarkers and build a prognostic model. …”
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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. …”
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From Molecules to Medicines: The Role of AI-Driven Drug Discovery Against Alzheimer’s Disease and Other Neurological Disorders by Mashael A. Alghamdi

“…Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. …”
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Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems by Natalya Denissova, Serik Nurakynov, Olga Petrova, Daniker Chepashev, Gulzhan Daumova, Alena Yelisseyeva

“…The analysis involved screening relevant studies on remote sensing, avalanche dynamics, and data processing techniques. …”
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Multimodal ultrasound radiomics containing microflow images for the prediction of central lymph node metastasis in papillary thyroid carcinoma by Jiangyuan Ben, Jiangyuan Ben, Qiying Yv, Pengfei Zhu, Junhao Ren, Pu Zhou, Guifang Chen, Ying He, Ying He

“…The same methods were applied to screen clinical features. Nine ML algorithms were used to construct clinical models, radiomics models and fusion models. …”
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High-flow nasal cannula therapy versus continuous positive airway pressure for non-invasive respiratory support in paediatric critical care: the FIRST-ABC RCTs by Padmanabhan Ramnarayan, Alvin Richards-Belle, Karen Thomas, Laura Drikite, Zia Sadique, Silvia Moler Zapata, Robert Darnell, Carly Au, Peter J Davis, Izabella Orzechowska, Julie Lester, Kevin Morris, Millie Parke, Mark Peters, Sam Peters, Michelle Saull, Lyvonne Tume, Richard G Feltbower, Richard Grieve, Paul R Mouncey, David Harrison, Kathryn Rowan

“…Background Despite the increasing use of non-invasive respiratory support in paediatric intensive care units, there are no large randomised controlled trials comparing two commonly used non-invasive respiratory support modes, continuous positive airway pressure and high-flow nasal cannula therapy. …”
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Application of Elastic networks and Bayesian networks to explore influencing factors associated with arthritis in middle-aged and older adults in the Chinese community by Tao Zhong, Tianlun Li, Jiapei Hu, Jiayi Hu, Li Jin, Yuxuan Xie, Bin Ma, Bin Ma, Dailun Hu

“…First, Elastic networks (ENs) were used to screen for features closely associated with arthritis, and we subsequently incorporated these features into the construction of the BNs model. …”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Moreover, it addresses the black box problem since the predictions are described to the end users thanks to the combination of LLMS with interpretable ML models (i.e. tree-based algorithms) using feature importance and natural language. …”
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The Future of Minimally Invasive GI and Capsule Diagnostics (REFLECT), October 2024 by Lea Østergaard Hansen, Alexandra Agache, Anastasios Koulaouzidis

“…The symposium also highlighted the significance of predictive models for patient selection and developments in panenteric CE. …”
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Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

“…Immunotherapy prediction models suggested a more favorable response to PD-1 treatment in the low IL1RAP expression group. …”
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Plasma metabolite biomarker identification study for the early detection of gastric cancer by Juan Zhu, Yida Huang, Bin Liu, Xue Li, Li Yuan, Le Wang, Kun Qian, Yingying Mao, Lingbin Du, Xiangdong Cheng

“…Ultra-performance liquid chromatography–mass spectrometry–based metabolomics methods were used to characterize the subjects’ plasma metabolic profiles and to screen and validate the GC biomarkers. Five machine learning algorithms (neural network, support vector machine, ridge regression, lasso regression and Naïve Bayes) were used to build a diagnostic model. …”
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Biomarker-driven drug repurposing for NAFLD-associated hepatocellular carcinoma using machine learning integrated ensemble feature selection by Subhajit Ghosh, Sukhen Das Mandal, Subarna Thakur

“…The incidence of non-alcoholic fatty liver disease (NAFLD), encompassing the more severe non-alcoholic steatohepatitis (NASH), is rising alongside the surges in diabetes and obesity. …”
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Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

“…This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. …”
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Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

“…The center of gravity method is used to address demand when constructing the quantitative function of out‐of‐stock loss. The NSGA‐II algorithm was selected to generate the results after the method comparison to ultimately determine the Pareto solution of the model. …”
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Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

“…These data support in-home use of the PRX VFT by the eye care provider for screening and monitoring in glaucoma, and may be extended to the screening and monitoring of other retinal, optic nerve and neurological diseases.Keywords: visual field test, glaucoma, home healthcare, prospective clinical trial…”
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Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning by Sijia Liu, Jiawei Luo, Chengqi He

“…Then, based on the key features screened out, a dynamic treatment recommendation system was constructed by using deep reinforcement learning algorithms, including Deep Deterministic Policy Gradien(DDPG), Deep Q-Network(DQN) and Batch-Constrained Q-learning(BCQ). …”
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