Agatha: Predicting Daily Activities from Place Visit History for Activity-Aware Mobile Services in Smart Cities by Byoungjip Kim, Seungwoo Kang, Jin-Young Ha, Junehwa Song

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Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework. by Xiaoyi Zhang, Yakang Zhang, Angelina Lilac Chen, Manning Yu, Lihao Zhang

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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

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Multi-modal radiomics features to predict overall survival of locally advanced esophageal cancer after definitive chemoradiotherapy by Nuo Yu, Yidong Wan, Lijing Zuo, Ying Cao, Dong Qu, Wenyang Liu, Lei Deng, Tao Zhang, Wenqing Wang, Jianyang Wang, Jima Lv, Zefen Xiao, Qinfu Feng, Zongmei Zhou, Nan Bi, Tianye Niu, Xin Wang

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MRI-based multiregional radiomics for preoperative prediction of Ki-67 expression in meningiomas: a two-center study by Ming Luo, Ming Luo, Guihan Lin, Duoning Chen, Duoning Chen, Weiyue Chen, Shuiwei Xia, Junguo Hui, Pengjun Chen, Minjiang Chen, Wangyang Ye, Wangyang Ye, Jiansong Ji

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Ability of the Short Physical Performance Battery Frailty Index to Predict Mortality and Hospital Readmission in Patients with Liver Cirrhosis by Mervat Essam Behiry, Sherif Mogawer, Ahmed Yamany, Maha Rakha, Rana Awad, Nahla Emad, Yasmine Abdelfatah

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Predicting local chemical order of NbTaTiHf medium-entropy alloys by cluster expansion method by Jing Zhang, Hao Xia, Zi-Yao Ma, Zhen-Dong Sha

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Predicting the Spread of Vessels in Initial Stage Cervical Cancer through Radiomics Strategy Based on Deep Learning Approach by Piyush Kumar Pareek, Prasath Alais Surendhar S, Ram Prasad, Govindaraj Ramkumar, Ekta Dixit, R. Subbiah, Saleh H. Salmen, Hesham S. Almoallim, S. S. Priya, S. Arockia Jayadhas

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Social Support Theory for Predicting Stress, Anxiety, and Job Burnout of Healthcare Workers in the Post-pandemic COVID-19 by Masoumeh Mohammadi Khanqah, Fataneh Bakhshi, Asieh Ashouri, Abolhasan Afkar

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Smart prediction of rock crack opening displacement from noisy data recorded by distributed fiber optic sensing by Shuai Zhao, Shao-Qun Lin, Dao-Yuan Tan, Hong-Hu Zhu, Zhen-Yu Yin, Jian-Hua Yin

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Prediction of sump oil growth rate towards gravitational settling of produced water in oilfield based on machine learning by Zhihua Wang, Cong Wang, Lan Meng, Xiangdong Qi, Jiajun Hong

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Development and validation of a nomogram for predicting hemoptysis recurrence in cystic bronchiectasis patients following bronchial artery embolization by Yuxin Duan, Weifan Sui, Zefeng Cai, Yimao Xia, Jianyun Li, Jianhua Fu

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Predicting Nitrous Oxide Emissions from China’s Upland Fields Under Climate Change Scenarios with Machine Learning by Tong Li, Yunpeng Li, Wenxin Cheng, Jufeng Zheng, Lianqing Li, Kun Cheng

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Multi‐Institutional MR‐Derived Radiomics to Predict Post‐Exenteration Disease Recurrence in Patients With T4 Rectal Cancer by Niall J. O'Sullivan, Fariba Tohidinezhad, Hugo C. Temperley, Mirac Ajredini, Bedirye Koyuncu Sokmen, Rumeysa Atabey, Leyla Ozer, Erman Aytac, Alison Corr, Alberto Traverso, James F. Meaney, Michael E. Kelly

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Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients by Tagayasu Anzai, Kenji Hirata, Ken Kato, Kohsuke Kudo

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Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm by Xuehui Fan, Ruixue Ye, Yan Gao, Kaiwen Xue, Zeyu Zhang, Jing Xu, Jingpu Zhao, Jun Feng, Yulong Wang

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A study on early diagnosis for fracture non-union prediction using deep learning and bone morphometric parameters by Hui Yu, Qiyue Mu, Zhi Wang, Yu Guo, Jing Zhao, Guangpu Wang, Qingsong Wang, Xianghong Meng, Xiaoman Dong, Shuo Wang, Jinglai Sun

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Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data by Jingyeong Jeong, Yoonseo Jeon, Hyungju Kim, Ji Won Yeom, Yu-Bin Shin, Sujin Kim, Seung Pil Pack, Heon-Jeong Lee, Taesu Cheong, Chul-Hyun Cho

“…This study aimed to propose a predictive machine learning model based on digital phenotypes for RLS diagnosis. …”
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Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network. by Itunuoluwa Isewon, Stephen Binaansim, Faith Adegoke, Jerry Emmanuel, Jelili Oyelade

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Spatial predictions of soil moisture across a longitudinal gradient in semiarid ecosystems using UAV and RGB sensors by Alexander Hernandez, Efrain Duarte, Peter Porter, Holden Brecht

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