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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Role of arachidonic acid metabolism in osteosarcoma prognosis by integrating WGCNA and bioinformatics analysis by Yaling Wang, Peichun HSU, Haiyan Hu, Feng Lin, Xiaokang Wei

“…An AA metabolism predictive model of the five AAMRGs were established by Cox regression and the LASSO algorithm. …”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…A prognostic model was constructed based on five selected IL(R)s using the LASSO Cox regression algorithm. …”
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CNN-Based Medical Ultrasound Image Quality Assessment by Siyuan Zhang, Yifan Wang, Jiayao Jiang, Jingxian Dong, Weiwei Yi, Wenguang Hou

“…At last, some tests are taken to evaluate the IQA models. They show that the CNN-based IQA is feasible and effective.…”
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Advances in the application of machine learning technology in the field of environmental health by ZHENG Yu, LI Cheng, HU Guiping, JIA Guang

“…However, the application of ML technology in the field of environmental health still faces challenges such as data quality, model interpretability, and interdisciplinary cooperation. …”
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Prevalence associations of various risk factors and arterial hypertension in male open urban population (by a one stage epidemiological study) by Е. V. Akimova, M. Yu. Akimov, E. I. Gakova, M. М. Kayumova, V. V. Gafarov, V. A. Kuznetsova

“…For the analysis of AH the data from cardiological screening was used, and surveying by psychosocial methods in algorithms of MONICA-MOPSY.Results. …”
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Toxoplasmosis seroprevalence in rheumatoid arthritis patients: A systematic review and meta-analysis. by Zahra Hosseininejad, Mehdi Sharif, Shahabeddin Sarvi, Afsaneh Amouei, Seyed Abdollah Hosseini, Tooran Nayeri Chegeni, Davood Anvari, Reza Saberi, Shaban Gohardehi, Azadeh Mizani, Mitra Sadeghi, Ahmad Daryani

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Individual differences in response to alcohol exposure in zebrafish (Danio rerio). by Heloysa Araujo-Silva, Jaquelinne Pinheiro-da-Silva, Priscila F Silva, Ana C Luchiari

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Prediction of EGFR mutations in non-small cell lung cancer: a nomogram based on 18F-FDG PET and thin-section CT radiomics with machine learning by Jianbo Li, Qin Shi, Yi Yang, Jikui Xie, Qiang Xie, Ming Ni, Xuemei Wang, Xuemei Wang

“…After selecting optimal radiomic features, four machine learning algorithms, including logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost), were used to develop and validate radiomics models. …”
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Detectability of Liver Steatosis and Fibrosis with Transient Elastography and Controlled Attenuation Parameter in Residents of St. Petersburg by V. P. Kovyazina, K. L. Raikhelson, M. K. Prashnova, E. V. Pazenko, L. K. Palgova, E. A. Kondrashina

“…Petersburg warrants improved diagnostic algorithms and routine preventive measures. Transient elastography with the controlled attenuation parameter estimation provides a convenient non-invasive screening for hepatic fibrosis and steatosis.…”
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Identification of novel cyclin-dependent kinase 4/6 inhibitors from marine natural products. by Abhijit Debnath, Rupa Mazumder, Anil Kumar Singh, Rajesh Kumar Singh

“…These 25 candidates underwent consensus molecular docking using seven distinct algorithms: AutoDockTools 4.2, idock, LeDock, Qvina 2, Smina, AutoDock Vina 1.2.0, PLANTS, and rDock. …”
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The Clinical Significance of the Dense Fine Speckled Immunofluorescence Pattern on HEp-2 Cells for the Diagnosis of Systemic Autoimmune Diseases by Michael Mahler, Marvin J. Fritzler

“…The indirect immunofluorescence (IIF) assay on HEp-2 cells is a commonly used test for the detection of ANA and has been recently recommended as the screening test of choice by a task force of the American College of Rheumatology. …”
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Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis by Hamed Hajishah, Danial Kazemi, Ehsan Safaee, Mohammad Javad Amini, Maral Peisepar, Mohammad Mahdi Tanhapour, Arian Tavasol

“…In total, 346 machine learning models were evaluated, with the most common algorithms being random forest, logistic regression, and gradient boosting. …”
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Critical review of OCT in clinical practice for the assessment of oral lesions by Fariba Esperouz, Domenico Ciavarella, Mauro Lorusso, Andrea Santarelli, Lorenzo Lo Muzio, Giuseppina Campisi, Lucio Lo Russo

“…This is further complicated by the introduction and increased trend to adopt artificial intelligence (AI) algorithms in imaging evaluation. Machine learning and deep learning algorithms have shown superior diagnostic sensitivity and accuracy compared to clinician judgment. …”
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

“…In addition, seven key genes, including PDK4, S100A8, HTRA1, CHI3L1, WT1, CDKN1B, and EGF, were screened by machine learning algorithm. Most of these genes exhibited low expression in renal tissue of DN patients and positive correlation with neutrophils, and their expressions were verified in an external dataset cell model. …”
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GPR65 is a novel immune biomarker and regulates the immune microenvironment in lung adenocarcinoma by Hanxu Zhou, Zhi Chen, Shuang Gao, Chaoqun Lian, Junjie Hu, Jin Lu, Lei Zhang

“…We screened differential genes (DEGs) in the immune and stromal components, and then screened modular genes by the WGCNA algorithm, which were intersected with DEGs and incorporated into the LASSO-COX regression model. …”
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Gait-Based Parkinson’s Disease Detection Using Recurrent Neural Networks for Wearable Systems by Carlos Rangel-Cascajosa, Francisco Luna-Perejón, Saturnino Vicente-Diaz, Manuel Domínguez-Morales

“…The ability of Deep Learning algorithms to identify complex features from clinical data has proven to be a promising approach in various medical domains as support tools. …”
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Design and predict the potential of imidazole-based organic dyes in dye-sensitized solar cells using fingerprint machine learning and supported by a web application by Mohamed M. Elsenety

“…Among of these, Deep Neural Network models of MLPRegressor algorithm based on the daylight fingerprint shows a significant coefficient of determination combined with the lowest errors. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Leveraging the Coxboost and random survival forest combination algorithm, we filtered out six DC-related genes on which a prognostic prediction model, DCRGS, was established. …”
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