Using apparent diffusion coefficient maps and radiomics to predict pathological grade in upper urinary tract urothelial carcinoma by Rile Nai, Kexin Wang, Shuai Ma, Zuqiang Xi, Yaofeng Zhang, Xiaodong Zhang, Xiaoying Wang

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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

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Magnetic-Resonance-Imaging Texture Analysis Predicts Early Progression in Rectal Cancer Patients Undergoing Neoadjuvant Chemoradiation by Valerio Nardone, Alfonso Reginelli, Fernando Scala, Salvatore Francesco Carbone, Maria Antonietta Mazzei, Lucio Sebaste, Tommaso Carfagno, Giuseppe Battaglia, Pierpaolo Pastina, Pierpaolo Correale, Paolo Tini, Gianluca Pellino, Salvatore Cappabianca, Luigi Pirtoli

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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

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Machine Learning Prediction of Storm‐Time High‐Latitude Ionospheric Irregularities From GNSS‐Derived ROTI Maps by Lei Liu, Y. Jade Morton, Yunxiang Liu

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Predict of the development of lipid distress syndrome in patients with a sustained response to antiviral therapy of chronic hepatitis C by D. Yu. Konstantinov, G. V. Nedugov

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Annual global dengue dynamics are related to multi-source factors revealed by a machine learning prediction analysis. by Haoyu Long, Yilin Chen, Jingru Feng, Jian Chen, Xue Zhang, Wenjie Han, Min Kang, Xiangjun Du

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Deep learning-based prediction of individualized Real-time FSH doses in GnRH agonist long protocols by Na Kong, Yu Xia, Zhilong Wang, Hui Zhang, Liyan Duan, Yingchun Zhu, Chenyang Huang, Guijun Yan, Jie Mei, Wujun Li, Haixiang Sun

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Development and validation of a radiomics-based nomogram for predicting pathological grade of upper urinary tract urothelial carcinoma by Yanghuang Zheng, Hongjin Shi, Shi Fu, Haifeng Wang, Xin Li, Zhi Li, Bing Hai, Jinsong Zhang

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Critical Frequency foF2 Variations at Korhogo Station from 1992 to 2001 Prediction with IRI-2012 by Karim Guibula, Jean Louis Zerbo, M’Bi Kaboré, Frédéric Ouattara

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Use of Google Earth Engine in predicting future giant cane (Arundinaria gigantea (Walter) Muhl.) restoration sites by Sanjeev Sharma

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New Methods for Predicting Strain Demand of Arctic Gas Pipelines across Permafrost under Frost Heave Displacement by Xinze Li, Qingbai Wu, Huijun Jin

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Mental Health Services Use Predicted by Number of Mental Health Problems and Gender in a Total Population Study by Maj-Britt Posserud, Astri J. Lundervold

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A Simpler Method for Predicting Weight Loss in the First Year after Roux-en-Y Gastric Bypass by John P. Sczepaniak, Milton L. Owens, William Garner, Farouk Dako, Kristin Masukawa, Samuel E. Wilson

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Accelerated fatigue strength prediction via additive manufactured functionally graded materials and high-throughput plasticity quantification by C. Bean, M. Calvat, Y. Nie, R.L. Black, N. Velisavljevic, D. Anjaria, M.A. Charpagne, J.C. Stinville

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Prediction on Permeability Coefficient of Continuously Graded Coarse-Grained Soils: A Data-Driven Machine Learning Method by Jinhua Wang, Haibin Ding, Lingxiao Guan, Yulin Wang

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Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study by Keisyanne Araujo-Moura, Letícia Souza, Tiago Almeida de Oliveira, Mateus Silva Rocha, Augusto César Ferreira De Moraes, Alexandre Chiavegatto Filho

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Machine Learning and Metabolomics Predict Mesenchymal Stem Cell Osteogenic Differentiation in 2D and 3D Cultures by Michail E. Klontzas, Spyros I. Vernardis, Aristea Batsali, Fotios Papadogiannis, Nicki Panoskaltsis, Athanasios Mantalaris

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Sonographic Assessment of Fetal Biometric Parameters and Maternal Height Ratio for Prediction of Cesarean Delivery due to Labor Dystocia by Wiarm Wadeng, Wanlaya Onwatanasarikul, Nop Khongthon, Monyada Pleankong, Sinart Prommas, Kornkarn Bhamarapravatana, Komsun Suwannarurk

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