The accuracy of the fullPIERS model in predicting adverse maternal and perinatal outcomes: evidence from a tertiary care maternity unit by Iury Gomes, Franz Marçal, João Victor de Carvalho Reis, Ana Paula dos Santos Silva, Lucas Sampaio, Leonardo Alves Moreira, Guilherme Lelis Costa, Mário Dias Correa Junior, Zilma Silveira Nogueira Reis, Jussara Mayrink

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Predicting seizure liability of small molecules using an in vitro multi-electrode array based assay coupled with modeling of brain disposition by David G. Belair, Rebecca Kohnken, Rebecca L. McCloud, Stephanie Sandoval, Jonathon Green, Wayne R. Buck, James S. Polakowski

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A diagnostic prediction model for anti-neutrophil cytoplasmic antibody associated vasculitis combined with glomerulonephritis based on machine learning algorithm by Wang Jian-mei, Zhu Ge-li, Cao Chen-lin, Peng Qing-quan

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Improved Risk Prediction of Acute Myocardial Infarction in Patients With Stable Coronary Artery Disease Using an Amino Acid-Assisted Model by Yi-Jing Zhao, Yong Li, Feng-Xiang Wang, Hao Lv, Yaoyao Qu, Lian-Wen Qi, Pingxi Xiao

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A scoping review of the use of artificial intelligence models in automated OCT analysis and prediction of treatment outcomes in diabetic macular oedema by Mohaimen Al-Zubaidy, Agnieszka Stankiewicz, Matthew Anderson, Jordan Reed, Veronica Corona, Rebecca Pope, Boguslaw Obara, Maged S. Habib, David H. Steel

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ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions by Maojie Xue, Ziang Xu, Xiang Wang, Jiajin Chen, Xinxin Kong, Shenxuan Zhou, Jiamin Wu, Yuhao Zhang, Yi Li, David C. Christiani, Feng Chen, Yang Zhao, Ruyang Zhang

“…Objectives: Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. …”
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Enhancing survival predictions in lung cancer with cystic airspaces: a multimodal approach combining clinical and radiomic features by Liang Yin, Jing Wang, Pingyou Fu, Lu Xing, Yuan Liu, Zongchang Li, Jie Gan

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Bridging the Gap: Limitations of Machine Learning in Real-World Prediction of Heavy Metal Accumulation in Rice in Hunan Province by Qing-Qian Peng, Xia Zhou, Hang Zhou, Ye Liao, Zi-Yu Han, Lu Hu, Peng Zeng, Jiao-Feng Gu, Rong Zhang

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Predicting immune status and gene mutations in stomach adenocarcinoma patients based on inflammatory response-related prognostic features by Huanjun Li, Jingtang Chen, Zhiliang Chen, Jingsheng Liao

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Predicting diabetic cardiomyopathy in type 2 diabetes: development and validation of a nomogram based on clinical and echocardiographic parameters by Zilang Luo, Zilang Luo, Damao Pi, Tianlan Xi, Wenli Jiang, Wenli Jiang, Feng Qiu, Jiadan Yang

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Physical activity and social-emotional learning in Canadian children: Multilevel perspectives within an early childhood education and care setting by Jasmine Zhang, Imogen M. Sloss, Nicola Maguire, Dillon T. Browne

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Predicting urban landslides in the hilly regions of Bangladesh leveraging a hybrid machine learning model and CMIP6 climate projections by Md․ Ashraful Islam, Musabbir Ahmed Arrafi, Mehedi Hasan Peas, Tanvir Hossain, Md Mehedi Hasan, Sanzida Murshed, Monira Jahan Tania

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Management of patients with venous thromboembolism and a high recurrence risk estimated by the Vienna Prediction Model: a prospective cohort study by Hana Šinkovec, Paul A. Kyrle, Lisbeth Eischer, Paul Gressenberger, Thomas Gary, Marianne Brodmann, Georg Heinze, Sabine Eichinger

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Cutting-edge approaches to specific energy prediction in TBM disc cutters: Integrating COSSA-RF model with three interpretative techniques by Jian Zhou, Zijian Liu, Chuanqi Li, Kun Du, Haiqing Yang

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Machine learning model interpretability using SHAP values: Applied to the task of classifying and predicting the nutritional content of different cuts of mutton by Li Wang, Xuchun Sun, Jing Liang, Zhiyuan Ma, Fei Li, Shengyan Hao, Baocang Liu, Long Guo, Xiuxiu Weng

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A machine learning model with crude estimation of property strategy for performance prediction of perovskite solar cells based on process optimization by Dan Li, Ernie Che Mid, Shafriza Nisha Basah, Xiaochun Liu, Jian Tang, Hongyan Cui, Huilong Su, Qianliang Xiao, Shiyin Gong

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Comparative analysis of machine learning models and explainable AI for agriculture drought prediction: A case study of the Ta-pieh mountains by Lichang Xu, Shaowei Ning, Xiaoyan Xu, Shenghan Wang, Le Chen, Rujian Long, Shengyi Zhang, Yuliang Zhou, Min Zhang, Bhesh Raj Thapa

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Data augmentation using SMOTE technique: Application for prediction of burst pressure of hydrocarbons pipeline using supervised machine learning models by Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Masdi B. Muhammad, Mohamad Hanif Md Saad, Najeebullah Lashari, Muhammad Hussain, Abdul Sattar Palli

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Machine learning based reduced-order models to predict spatiotemporal dynamics of soil carbon and biomass yield of different bioenergy crops by Sagar Gautam, Umakant Mishra, Corinne D. Scown

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Physics-informed and data-driven thermal modeling and temperature field prediction for thermal field-assisted direct ink writing with PDMS by Xinhua Yao, Yuhan Jiang, Lixin Tian, Xiang Li, Yong He

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