Application of federated learning in predicting breast cancer by Chai Jiarui

“…The prediction and diagnosis of breast cancer relies on multimodal data, such as imaging, genetic information, and patient lifestyle habits. …”
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Accuracy of smartwatches in predicting distance running performance by Jiansong Dai, Gangrui Chen, Zhonghe Gu, Yuxuan Qi, Kai Xu

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Explore Machine Learning's Prediction of Football Games by Pan Bomao

“…The aim of this study is to predict the outcome and score of football matches. …”
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Axial Compressor Stall and Surge Prediction by Measurements by H. Hönen

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Fuzzy Approach in Rail Track Degradation Prediction by Mostafa Karimpour, Lalith Hitihamillage, Najwa Elkhoury, Sara Moridpour, Reyhaneh Hesami

“…Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work. With the restrictions on financial support, the rail transport authorities are in pursuit of improved modern methods, which can provide a precise prediction of rail maintenance timeframe. …”
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Digital generation in the context of predicting the professional future by E. F. Zeer, N. G. Tserkovnikova, V. S. Tretyakova

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Prediction of Blasting Fragmentation Based on GWO-ELM by Zhengzhao Jia, Ziling Song, Junfu Fan, Juyu Jiang

“…Taking No. 2 open-pit coal mine of Dananhu as an example, seven factors including the rock tensile strength, compressive strength, hole spacing, row spacing, minimum resistance line, super depth, and specific charge are selected as the input factors of the prediction model. The average size of blasting fragmentation X50 is selected as the output factor of the prediction model and compared with the results of PSO-ELM and ELM. …”
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DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE by Edin Osmanbegović, Mirza Suljić

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Modeling and Prediction of Momentum Wheel Speed Data by Jichao Li, Xiaxia Wang, Chaobo Chen, Song Gao

“…The future data trend is predicted by the proposed model. Simulation results show that the prediction algorithm can achieve the across cycle prediction of the MW speed data.…”
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Intelligent Prediction of Sieving Efficiency in Vibrating Screens by Bin Zhang, Jinke Gong, Wenhua Yuan, Jun Fu, Yi Huang

“…In order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. …”
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Political Prediction and Communication Problems in Aeschylus’ Agamemnon by Laisvūnas Čekavičius

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Prediction of Ubiquitination Sites Using UbiNets by Sarthak Yadav, Manoj Gupta, Ankur Singh Bist

“…Various machine learning techniques are taken for prediction of ubiquitination sites in protein sequences. …”
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Prediction of Conducted Emissions in Satellite Power Buses by Giordano Spadacini, Flavia Grassi, Diego Bellan, Sergio A. Pignari, Filippo Marliani

“…This work reports a modeling methodology for the prediction of conducted emissions (CE) in a wide frequency range (up to 100 MHz), which are generated by dc/dc converters and propagate along the power buses of satellites. …”
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Out-of-Sample Predictability of the Equity Risk Premium by Daniel de Almeida, Ana-Maria Fuertes, Luiz Koodi Hotta

“…Acknowledging the different predictability of the equity premium in expansions and recessions, this paper proposes an approach that combines equity premium forecasts from two-state regression models using an agreement technical indicator as the observable state variable. …”
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Cultural and personal values interact to predict divorce by Sari Mentser, Lilach Sagiv

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Early Stroke Prediction Methods for Prevention of Strokes by Mandeep Kaur, Sachin R. Sakhare, Kirti Wanjale, Farzana Akter

“…This paper is proposing time series-based approaches such as LSTM, biLSTM, GRU, and FFNN that can handle time series-based predictions to make useful decisions. The experimental research outcome reveals that all the algorithms taken up for the research study perform well on the prediction problem of early stroke detection, but GRU performs the best with 95.6% accuracy, whereas biLSTM gives 91% accuracy and LSTM gives 87% accuracy and FFNN gives 83% accuracy. …”
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Data Analysis for Predictive Maintenance of Servo Motors by Oguz Girit, Gurcan Atakok, Sezgin Ersoy

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Developing Seismic Risk Prediction Functions for Structures by Naveed Ahmad, Qaisar Ali, Muhammad Adil, Akhtar Naeem Khan

“…The methodology is tested for seismic risk assessment of the considered typology in recent 2005 Kashmir earthquake, which is reasonably predicted. Future development of the methodology is required with additional experimental tests on rubble stone masonry material in order to increase confidence in future applications.…”
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Analyzing the Application of Machine Learning in Anemia Prediction by Li Yuxi

“…This paper explores the applications of machine learning in the prediction of anemia, highlighting its potential to revolutionize clinical diagnosis and management. …”
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Fundamentals and Methods for T- and B-Cell Epitope Prediction by Jose L. Sanchez-Trincado, Marta Gomez-Perosanz, Pedro A. Reche

“…Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.…”
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