The influence of obesity on IOS parameters in asthma, COPD, and other lung diseases: analyzed by random forest by Thomas Ringbaek, Lars Froelund, Jann Mortensen, Henrik H. El Ali

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Analyzing Momentum Shifts in Tennis: A Machine-Learning Approach to Predicting Match Outcomes by Yuean Xia, Changfeng Li, Tanran Zhang

Subjects: “…momentum analysis…”
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Liver fibrosis progression analyzed with AI predicts renal decline by Dan-Qin Sun, Jia-Qi Shen, Xiao-Fei Tong, Ya-Yun Ren, Hai-Yang Yuan, Yang-Yang Li, Xin-Lei Wang, Sui-Dan Chen, Pei-Wu Zhu, Xiao-Dong Wang, Christopher D. Byrne, Giovanni Targher, Lai Wei, Vincent W.S. Wong, Dean Tai, Arun J. Sanyal, Hong You, Ming-Hua Zheng

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Analyzing the Application of Machine Learning in Anemia Prediction by Li Yuxi

“…Machine learning techniques provide innovative solutions by analyzing complex datasets that incorporate questionnaire, clinical features, demographic information, and laboratory results, thereby enhancing the accuracy of anemia predictions. …”
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Topological Attention-Based Convolution Neural Networks in Analyzing and Predicting Particulate Matter Pollution Level by Zixin Lin, Nur Fariha Syaqina Zulkepli, Mohd Shareduwan Mohd Kasihmuddin, R. U. Gobithaasan

“…PM10 category labels were predicted 6, 12, and 24 hours ahead. Data from 15 stations in Malaysia (2019–2020) were used, with feature selection based on correlation analysis. …”
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Models for analyzing and forecasting share prices on the stock exchange by Р. Пізнак, Т. Ліхоузова

Subjects: “…intelligent data analysis…”
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Analyzing Predictive Indicators of Fever and Sepsis after Percutaneous Nephrolithotomy by Gautam Zalavadiya, S Santhosh, Lata Ajay Tapnikar, Nikhil Ramesh Vaidya, Vivek Amritbhai Patel, Nilam V. Patel

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A robust and statistical analyzed predictive model for drug toxicity using machine learning by Deepak Rawat, Rohit Bajaj, Rachit Manchanda, Ankush Mehta, Prabhu Paramasivam, Suraj Kumar Bhagat, Abinet Gosaye Ayanie

“…Abstract Over the years, toxicity prediction has been a challenging task. Artificial intelligence and machine learning provide a platform to study toxicity prediction more accurately with a reduced time span. …”
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Software pipeline for predicting and analyzing the structure of the receptor–ligand by A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova

“…Such a pipeline involves a complex algorithm, from predicting the structure of the receptor to searching and analyzing the interaction of ligands with the receptor. …”
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Predicting the prognosis of patients with sudden sensorineural hearing loss by analyzing the audiometric curve of the unaffected ear by Xuan Sun, Yahan Zhao, Yi Li

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Prediction of suicide using web based voice recordings analyzed by artificial intelligence by Agnieszka Ewa Krautz, Julia Volkening, Janik Raue, Christian Otte, Simon B. Eickhoff, Eike Ahlers, Jörg Langner

“…In this study, we utilized ML in a case-control design, we predicted completed suicides using publicly available, web-based, real-world voice data, and treating speech as a biomarker. …”
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Modeling, Small-Signal Stability Analyzing and Implementing of an Inverter-Based Distributed Generation with Feed-forwarded Model Predictive Controller by abdolhossein saleh

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Analyzing Financial Stability by Predicting Bankruptcy Situations with Machine Learning by Mohd Naved, Ravi Kumar, Shaiku Saheb

“…Machine learning (ML) may help in bankruptcy prediction by analyzing massive quantities of historical financial data, identifying trends and anomalies that indicate trouble, and developing predictive models to estimate the possibility of default. …”
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Predictive Modelling of Protest Event Signatures: Analyzing Temporal Dynamics and Digital Activism Discourse Across Global Movements by Amila Chethana Nanayakkara, B. T. G. Samantha Kumara, R. M. Kapila Tharanga Rathnayaka

“…This research introduced a predictive modeling framework to analyze the temporal dynamics of social media discourse during three global movements: the Mahsa Amini Protests (2022), South African Unrest (2021), and the Black Lives Matter Movement (2020). …”
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MTFAP: a comprehensive platform for predicting and analyzing master transcription factors by Jianyuan Zhou, Haojie Yu, Chunhui Lou, Min Yang, Yanshang Li, Qian Yang, Shuhan Li, Chunwang Ji, Song Li, Shuang Wang, Haotian Cao, Xuecang Li, Lian Liu

“…Therefore, we developed a master transcription factors prediction and analysis web resource (MTFAP). MTFAP is a comprehensive web tool designed to predict and analyze MTFs with different data types. …”
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Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage by Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Woon-Ha Hwang, Jae-Ki Chang, Nam-Jin Chung, Wan-Gyu Sang

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Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk by Mohammad Amin Hemmati, Marzieh Monemi, Shima Asli, Sina Mohammadi, Behina Foroozanmehr, Dariush Haghmorad, Valentyn Oksenych, Majid Eslami

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Prediction of bronchopulmonary dysplasia course in children by analyzing clinico-biochemical indicators by L. M. Chernenko

“…The aim of the work is to improve the prediction of bronchopulmonary dysplasia course in children by analyzing the relationships between clinical and biochemical indicators and determine the risk factors for an unfavorable course of the disease. …”
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Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…The second model predicts the transition from multiple AAb+ to the onset of T1D. …”
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Integrating bibliometrics and deep learning to analyze emerging trends and predict future directions in photoelectrochemical water splitting for hydrogen production: A Scopus-database driven study by Md. Saiful Islam, Sadit Bihongo Malitha, Md. Abu Sayid Mia, Md. Zahangir Alam

“…The progress of photoelectrochemical water splitting for hydrogen production was systematically analyzed based on articles, countries, authors, institutions, journals, and cited references. …”
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