Adaptive anomaly detection disruption prediction starting from first discharge on tokamak by X.K. Ai, W. Zheng, M. Zhang, Y.H. Ding, D.L. Chen, Z.Y. Chen, B.H. Guo, C.S. Shen, N.C. Wang, Z.J. Yang, Z.P. Chen, Y. Pan, B. Shen, B.J. Xiao, J-TEXT team

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Predicting Neoplastic Gallbladder Polyps: The Role of Current Surgical Indications and Preoperative Images by Ik Hyun Jo, Chang Nyol Paik, Hong Geun Ahn, Dong Do You, Jae Hyun Han, Hyun A Kim

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Predictive biomarkers for cardiometabolic risk in postmenopausal women: insights into visfatin, adropin, and adiponectin by Anna Maria Cybulska, Daria Schneider-Matyka, Ireneusz Walaszek, Mariusz Panczyk, Dorota Ćwiek, Anna Lubkowska, Elżbieta Grochans, Kamila Rachubińska, Katarzyna Malewicz, Mariusz Chabowski, Mariusz Chabowski

“…Furthermore, circulating adiponectin positively correlated with HDL, and negatively with HOMA-IR.ConclusionsAdiponectin is a promising biomarker for predicting cardiometabolic risk in postmenopausal women.…”
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Interactions between ABC gene polymorphisms and processing speed in predicting depression severity by Meijiang Jin, Lei Ji, Maojia Ran, Yan Bi, Hang Zhang, Yuanmei Tao, Hanmei Xu, Shoukang Zou, Hong Zhang, Tao Yu, Li Yin

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Empirical prediction intervals applied to short term mortality forecasts and excess deaths by Ricarda Duerst, Jonas Schöley

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Skillful prediction of Indian Ocean Dipole index using machine learning models by J.V. Ratnam, Swadhin K. Behera, Masami Nonaka, Kalpesh R. Patil

“…In this study, we evaluated six machine learning models for their skill in predicting the Indian Ocean Dipole (IOD). The results based on the IOD index predictions at 1–8 month lead time indicate that the AdaBoost model with Multi-Layer Perceptron as the base estimator, AdaBoost(MLP), to perform better than the other five models in predicting the IOD index at all lead times. …”
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Severe deviation in protein fold prediction by advanced AI: a case study by Jacinto López-Sagaseta, Alejandro Urdiciain

“…Significant deviation between experimental structures and AI-predicted models echoes the presence of unusual conformations, insufficient training data and high complexity in protein folding that can ultimately lead to current limitations in protein structure prediction.…”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…A user-friendly interface was developed for instant SE prediction of carbon fiber reinforced mortar, requiring only essential input parameters.…”
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Stroke Lesion Prediction by Bille-Viper-Segmentation with Tandem-MU-net Model by Beevi Fathima, N Santhi Dr, N Ramasamy Dr

“…Stroke is a critical condition marked by the death of brain cells due to inadequate blood flow, necessitating improved predictive models for stroke lesions. The accuracy and flexibility required to forecast and classify stroke lesions is lacking in current approaches, which compromise patient outcomes. …”
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Leveraging machine learning to predict residential location choice: A comparative analysis by Vahid Noferesti, Hamid Mirzahossein

“…This often leads to biased predictions, favoring popular choices over less common ones. …”
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Comparative Analysis of Diabetes Prediction Models Using the Pima Indian Diabetes Database by Zhao Yize

“…This study provides an in-depth review and comparison of diabetes prediction models using the Pima Indian Diabetes database. …”
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Application Research of Cross-Attention Mechanism for Traffic Prediction Based on Heterogeneous Data by Feng Zhihao

“…Intelligent transportation systems need to be developed with precise traffic flow predictions to reduce traffic accidents, improve overall urban mobility, and mitigate congestion. …”
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Ultrasound Radiogenomics-based Prediction Models for Gene Mutation Status in Breast Cancer by Zhai Yue, Tan Dianhuan, Lin Xiaona, Lv Heng, Chen Yan, Li Yongbin, Luo Haiyu, Dan Qing, Zhao Chenyang, Xiang Hongjin, Zheng Tingting, Sun Desheng

Subjects: “…|ultrasound|radiogenomics|breast cancer|gene mutation|prediction models…”
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A Multivariate prediction model for amlodipine therapeutic efficacy in pediatric primary hypertension by Yao Lin, Hui Wang, Yaqi Li, Yang Liu, Yanyan Liu, Hongwei Zhang, Yanjun Deng, Lin Shi

“…BackgroundThere are currently no biomarker-based prediction models for amlodipine therapeutic efficacy in pediatric hypertension. …”
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Deep Learning-Based Energy Consumption Prediction Model for Green Industrial Parks by Chaoan Lai, Yina Wang, Jianhua Zhu, Xuequan Zhou

“…The model shows a closer fit to the original series trend and more accurate predictions at extreme points, aligning more closely with actual values.…”
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Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

“…This study investigates the prediction of the aerodynamic characteristics of Flettner rotors through three deep learning models. …”
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A CD36-based prediction model for sepsis-induced myocardial injury by Yun Xie, Hui Lv, Daonan Chen, Peijie Huang, Zhigang Zhou, Ruilan Wang

“…This study aims to develop a predictive model for SIMI using plasma CD36 levels. …”
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Positional embeddings and zero-shot learning using BERT for molecular-property prediction by Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, Kyuri Jo, Young-Seob Jeong

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Enhancing environmental monitoring of harmful algal blooms with ConvLSTM image prediction by Sung Jae Kim, Yongbok Cho

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Robust adaptive optimization for sustainable water demand prediction in water distribution systems by Ke Wang, Jiayang Meng, Zhangquan Wang, Kehua Zhao, Banteng Liu

Subjects: “…Water demand prediction…”
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