Developing and validating an artificial intelligence-based application for predicting some pregnancy outcomes: a multi-phase study protocol by Fatemeh Shabani, Ata Jodeiri, Sakineh Mohammad‑Alizadeh‑Charandabi, Fatemeh Abbasalizadeh, Jafar Tanha, Mojgan Mirghafourvand

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Multi‐Omic Analysis Reveals a Lipid Metabolism Gene Signature and Predicts Prognosis and Chemotherapy Response in Thyroid Carcinoma by Yuqin Tu, Yanchen Chen, Linlong Mo, Guiling Yan, Jingling Xie, Xinyao Ji, Shu Chen, Changchun Niu, Pu Liao

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A visualized nomogram to predict intravenous immunoglobulin resistance in Kawasaki disease: a study based on the population in Southern China by Xinping Lin, Yunsong Li, Sihuang Chen, Shiteng Lin, Xiaoqing Yang, Wei Zhuang

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Multimodal Deep Learning for Cardiovascular Risk Stratification: Integrating Retinal Biomarkers and Cardiovascular Signals for Enhanced Heart Attack Prediction by K. Sathya, G. Magesh

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Predicting Upper body Muscle Activation Patterns in Paralympic Cross-Country Skiing Using Neural Networks and Accelerometer Data by Barioudi Hatim, Felderhoff Thomas, Mrachacz-Kersting Natalie

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Longitudinal MRI‐Driven Multi‐Modality Approach for Predicting Pathological Complete Response and B Cell Infiltration in Breast Cancer by Yu‐Hong Huang, Zhen‐Yi Shi, Teng Zhu, Tian‐Han Zhou, Yi Li, Wei Li, Han Qiu, Si‐Qi Wang, Li‐Fang He, Zhi‐Yong Wu, Ying Lin, Qian Wang, Wen‐Chao Gu, Chang‐Cong Gu, Xin‐Yang Song, Yang Zhou, Dao‐Gang Guan, Kun Wang

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A deep learning approach for early prediction of breast cancer neoadjuvant chemotherapy response on multistage bimodal ultrasound images by Jiang Xie, Jinzhu Wei, Huachan Shi, Zhe Lin, Jinsong Lu, Xueqing Zhang, Caifeng Wan

“…In this study, a novel convolutional neural network model with bimodal layer-wise feature fusion module (BLFFM) and temporal hybrid attention module (THAM) is proposed, which uses multistage bimodal ultrasound images as input for early prediction of the efficacy of neoadjuvant chemotherapy in locally advanced breast cancer (LABC) patients. …”
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Prediction of vasopressor needs in hypotensive emergency department patients using serial arterial blood pressure data with deep learning by Yeongho Choi, Ki Hong Kim, Yoonjic Kim, Dong Hyun Choi, Yoon Ha Joo, Sae Won Choi, Kyoung Jun Song, Sang Do Shin

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The molecular subtype based on cell cycle-related gene signature predicts the prognosis and chemotherapy and immunotherapy response in gastric cancer by Rishun Su, Jia Chen, Chen Dai, Songcheng Yin, Haoming Chen, Xuezeng Sun, Zhaoxin Fang, Changhua Zhang, Jingyao Chen, Liang Gu

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Utility of the 2019 EULAR/ACR SLE classification criteria for predicting mortality and hospitalisation: development and cross-validation of ominosity score by Ali Duarte-García, Gabriel Figueroa-Parra, Andrew C Hanson, Cynthia Crowson, Kamil E Barbour, Alain Sanchez-Rodriguez, María C Cuéllar-Gutiérrez, Mariana González-Treviño, José A Meade-Aguilar

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Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences by Zhu Liang, Jiamin Li, Yihan Tang, Yaxuan Zhang, Chunyuan Chen, Siyuan Li, Xuefeng Wang, Xinyan Xu, Ziye Zhuang, Shuyan He, Biao Deng

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Prediction of functional outcomes in aneurysmal subarachnoid hemorrhage using pre-/postoperative noncontrast CT within 3 days of admission by Pengzhan Yin, Jiaqi Wang, Chao Zhang, Yongxiang Tang, Xiankuo Hu, Hongmin Shu, Jun Wang, Bin Liu, Yongqiang Yu, Yunfeng Zhou, Xiaohu Li

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Longitudinal CE-MRI-based Siamese network with machine learning to predict tumor response in HCC after DEB-TACE by Nan Wei, René Michael Mathy, De-Hua Chang, Philipp Mayer, Jakob Liermann, Christoph Springfeld, Michael T Dill, Thomas Longerich, Georg Lurje, Hans-Ulrich Kauczor, Mark O. Wielpütz, Osman Öcal

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A machine learning based radiomics approach for predicting No. 14v station lymph node metastasis in gastric cancer by Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Xiangli Li, Xiangchao Song, Xiangchao Song, Xiangchao Song, Xiangchao Song, Lingwei Wang, Lingwei Wang, Lingwei Wang, Lingwei Wang, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye

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Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study by An Zhou, Kui Chen, Kui Chen, Yonghui Wei, Qu Ye, Qu Ye, Yuanming Xiao, Rong Shi, Jiangang Wang, Wei-Dong Li

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Robust prediction of glioma prognosis by hypoxia-induced ferroptosis genes: VEGFA-XBP1 co-expression for salvage therapy by Zhou Liwei, Lu Hanwen, Zhao Wenpeng, Yu Weijie, Chen Sifang, Zhang Bingchang, Li Zhangyu, Gao Xin, Li Wenhua, Mao Jianyao, Xie Yuanyuan, Tan Guowei, Wang Zhanxiang

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Predictive nomogram for postoperative lower-limb deep vein thrombosis in patients undergoing endoscopic endonasal surgery during hospitalization: a retrospective cohort study by Hai Peng, Ruofei Yuan, Zhe Zhang, Ying Wang, Xingchao Wang, Bo Wang, Peng Li

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Predicting damage in notched functionally graded materials plates through extended finite element method based on computational simulations by Hakim Siguerdjidjene, Amin Houari, Kouider Madani, Salah Amroune, Mohamed Mokhtari, Barhm Mohamad, Chellil Ahmed, Abdelkrim Merah, Raul D.S.G. Campilho

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Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM by Jianquan Yao, Jiajia Nie, Chaofeng Li

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Magneto Inductive (MI) Channel Variables Prediction Through Machine Learning Linear Regression Method, for Underwater and Underground WSNs by Aman Muhammad, Fuzhong Li, Syed Agha Hassnain Mohsan, Zahid Ullah Khan, Waqar Khan, Sajid Ullah Khan, Ziqi Han, Faheem Khan

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