Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis by Xiangui Lv, Daiqiang Liu, Xinwei Chen, Lvlin Chen, Xiaohui Wang, Xiaomei Xu, Lin Chen, Chao Huang

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Predicting Binding Affinity of Some Imatinib Derivatives as BCR-ABL Tyrosine Kinase Inhibitors Based on Monte Carlo Optimization by Shahram Lotfi, Shahin Ahmadi, Sharare Vardast Baghmisheh, Ali Almasirad

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A novel self-attentive deep learning for predicting pregnancy outcome after hysteroscopic adhesiolysis in patients with intrauterine adhesions by Yueqi Li, Jieying Zheng, Yong Shi, Jiansheng Wu, Danhong Peng, Jun Wang

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Effects of Subsetting by Carbon Content, Soil Order, and Spectral Classification on Prediction of Soil Total Carbon with Diffuse Reflectance Spectroscopy by Meryl L. McDowell, Gregory L. Bruland, Jonathan L. Deenik, Sabine Grunwald

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Pathways to improving MIR prediction accuracy for soil carbon, nitrogen and pH using external libraries at national scale by Felipe Bachion de Santana, Giulia Bondi, Karen Daly

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Nomogram Predicting In-Hospital Mortality in Patients with Myocardial Infarction Treated with Primary Coronary Interventions Based on Logistic and Angiographic Predictors by Lukasz Gawinski, Anna Milewska, Michal Marczak, Remigiusz Kozlowski

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Multi-omics prediction of axillary treatment response and tumour microenvironment alterations in lymph node-positive luminal breast cancer by Teng Ma, Zirui Wang, Zhe Zhou, Yongmei Wang, Tianyi Ma, Xiangping Liu, Yan Mao, Haibo Wang

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Early dynamics of clinical and laboratory parameters predict primary refractory disease in patients with metastatic urothelial carcinoma receiving atezolizumab by Guru Sonpavde, Paul J Catalano, Franziska Michor, Christopher J Graser, Thomas O McDonald

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A unique statistical framework to predict the health of a machine by utilizing the vibration features of rolling element bearing data by Saima Bhatti, Fozia Shaikh, Asif Mansoor, Asif Ali Shaikh

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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

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A novel deep learning framework with artificial protozoa optimization-based adaptive environmental response for wind power prediction by Sangkeum Lee, Mohammad H. Almomani, Saleh Ali Alomari, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Amir H. Gandomi, Laith Abualigah

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A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases by Norma Latif Fitriyani, Muhammad Syafrudin, Nur Chamidah, Marisa Rifada, Hendri Susilo, Dursun Aydin, Syifa Latif Qolbiyani, Seung Won Lee

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Natural Language Processing-Based Deep Learning to Predict the Loss of Consciousness Event Using Emergency Department Text Records by Hang A. Park, Inyeop Jeon, Seung-Ho Shin, Soo Young Seo, Jae Jun Lee, Chulho Kim, Ju Ok Park

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Enhancing mortality prediction after coronary artery bypass graft: a machine learning approach utilizing EuroScore by Emad Hijazi

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A Method for Predicting the Remaining Life of Lithium-Ion Batteries Based on an Improved Dempster–Shafer Evidence Theory Framework by Tongrui Zhang, Hao Sun

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Prediction of asthma outpatients using cumulative particulate matter and machine learning algorithms: a case study in Adiyaman, Turkey by Abdurrahman Özbeyaz, Mustafa Yıldırım, Fatih Tufaner

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A hybrid data assimilation method based on real-time Ensemble Kalman filtering and KNN for COVID-19 prediction by SongTao Zhang, LiHong Yang

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Prediction of postoperative visual cognitive impairment using graph theory and machine learning based on resting-state brain networks by Songbin Liu, Zhaoshun Jiang, Pei Ye, Feidong Lv, Fei Tao, Yuxi Cai, Lina Yi, Shihong Li, Guoqing Wu, Jun Zhang, Weidong Gu

“…However, effective preoperative prediction methods remain lacking. We developed a machine learning model using graph theory analysis of resting-state functional connectivity networks to predict postoperative visual cognitive impairment. …”
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Artificial Neural Network Approach for Predicting Enzymatic Hydrolysis of Steam Exploded Pine Wood Chip in Mild Alkaline Pretreatment by Hyeon Cheol Kim, Si Young Ha, Jae-Kyung Yang

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Development of a clinical-radiological nomogram for predicting severe postoperative peritumoral brain edema following intracranial meningioma resection by Chen Bo, Geng Ao, Lu Siyuan, Lu Siyuan, Wu Ting, Wang Dianjun, Zhao Nan, Shan Xiuhong, Deng Yan, Sun Eryi

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