Stroke Prediction Based on Machine Learning by Zhang Yuhan

“…Machine learning technology can analyze patients’ historical health data and biometrics to identify high-risk individuals in a timely manner, thereby effectively predicting stroke.This paper evaluates the predictive performance Random Forest and Support Vector Machine (SVM). …”
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Efficient Structured Prediction with Transformer Encoders by Ali Basirat

“… Finetuning is a useful method for adapting Transformer-based text encoders to new tasks but can be computationally expensive for structured prediction tasks that require tuning at the token level. …”
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An Overview of Pavement Degradation Prediction Models by Amir Shtayat, Sara Moridpour, Berthold Best, Shahriar Rumi

“…The paper also identifies and summarizes the most influencing parameters in road pavement condition prediction models and presents the strength and weaknesses of each prediction model. …”
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Nonlinear Autoregressive Model for Stability and Prediction by Salim M. Ahmad, Anas S. Youns, Manal S. Hamdi

“…A proposed nonlinear autoregressive model was employed to predict daily new COVID-19 infections in Iraq. This model was applied to actual COVID-19 data from 3 months in 2022 and met the stability criteria set by the proposed nonlinear regression model, based on a model developed by Japanese scientist Ozaki. …”
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Prediction of IL4 Inducing Peptides by Sandeep Kumar Dhanda, Sudheer Gupta, Pooja Vir, G. P. S. Raghava

“…These results indicate that it is possible to predict IL4 inducing peptides with reasonable precession. …”
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Asthma Symptoms Do not Predict Spirometry by Robert L Cowie, Margot F Underwood, Stephen K Field

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Prediction of hemolytic peptides and their hemolytic concentration by Anand Singh Rathore, Nishant Kumar, Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…Abstract Peptide-based drugs often fail in clinical trials due to their toxicity or hemolytic activity against red blood cells (RBCs). Existing methods predict hemolytic peptides but not the concentration (HC50) required to lyse 50% of RBCs. …”
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Prediction of Chloride Penetration into Hardening Concrete by Wei-Jie Fan, Xiao-Yong Wang

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Components and predictability of pollutants emission intensity by Z. Farajzadeh, M.A. Nematollahi

“…However, the prediction error for carbon dioxide emission intensity was much higher.…”
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Metrology Needs for Predicting Concrete Pumpability by Myoungsung Choi, Chiara F. Ferraris, Nicos S. Martys, Didier Lootens, Van K. Bui, H. R. Trey Hamilton

“…Thus, developing realistic and simple measurement techniques and prediction tools is a financial and logistical challenge that is out of reach for small research labs and many private companies in the concrete construction industry. …”
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Prediction of Bleeding Etiology: The Clinician is Vindicated! by Stephen E Congly, Alexander I Aspinall

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Bubble Departure Diameter Prediction Uncertainty by Marko Matkovič, Boštjan Končar

“…This paper presents quality assessment of a mechanistic modelling for bubble departure diameter prediction during pool boiling condition. In contrast to flow boiling process only buoyancy force with opposing surface tension force was considered as the responsible mechanisms for bubble departure. …”
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Data Visualization and Prediction Model Analysis by Hua Ziyi

“…The purpose of this paper is to study the application of data visualization and compare different prediction models. In this work, I present three different prediction models and apply them on the US airline industry datasets by using Python as the programming language. …”
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Predictive learning as the basis of the testing effect by Haopeng Chen, Cathy Hauspie, Kate Ergo, Cristian Buc Calderon, Tom Verguts

“…Emergent frameworks propose fundamental (Hebbian and predictive) learning principles as its basis. Predictive learning posits that learning occurs based on the contrast (error) between a prediction and the feedback on that prediction (prediction error). …”
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Sustainable foam glass property prediction using machine learning: A comprehensive comparison of predictive methods and techniques by Mohamed Abdellatief, Leong Sing Wong, Norashidah Md Din, Ali Najah Ahmed, Abba Musa Hassan, Zainah Ibrahim, G. Murali, Kim Hung Mo, Ahmed El-Shafie

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A Grey NGM(1,1,k) Self-Memory Coupling Prediction Model for Energy Consumption Prediction by Xiaojun Guo, Sifeng Liu, Lifeng Wu, Lingling Tang

“…Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. …”
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Bleeding risk and prediction model to predict bleeding risk of tissue biopsy for definitive diagnosis in patients with suspected amyloidosis by Watsamon Uraiwan, Pirun Saelue

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Short- to Medium-Term Weather Forecast Skill of the AI-Based Pangu-Weather Model Using Automatic Weather Stations in China by Siyi Xu, Yize Zhang, Junping Chen, Yunlong Zhang

Subjects: “…numerical weather prediction…”
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Multi-Step-Ahead Prediction of Chaotic Time Series: Self-Healing Algorithm for Restoring Values at Non-Predictable Points by Vasilii A. Gromov, Korney K. Tomashchuk, Alexey Rukavishnikov A.

“…The introduction of the concept of non-predictable points enabled to avoid the exponential growth of the prediction error as a function of the number of steps ahead, which made it possible to develop algorithms that predict many Lyapunov times (and many steps) ahead – the price for this turned out to be that some points remained non-predictable. …”
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Establishment and validation of predictive model of ARDS in critically ill patients by Senhao Wei, Hua Zhang, Hao Li, Chao Li, Ziyuan Shen, Yiyuan Yin, Zhukai Cong, Zhaojin Zeng, Qinggang Ge, Dongfeng Li, Xi Zhu

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