Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models by Xiaoxue Yang, Yajie Zou, Jinjun Tang, Jian Liang, Muhammad Ijaz

“…Accurate prediction of traffic information (i.e., traffic flow, travel time, traffic speed, etc.) is a key component of Intelligent Transportation System (ITS). …”
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External validation of radiobiological models for local control prediction in lung cancer patients treated with stereotactic body radiation therapy by Bao-Tian Huang, Pei-Xian Lin, Ying Wang, Li-Mei Luo

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Investigating the Predictive Capabilities of MARS for Biomass Pyrolysis Kinetics: A Case Study on an Oil Palm Empty Fruit Bunch by Junaid Ahmad, Chawalit Ngamcharussrivichai, Imtiaz Ali

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Optic Nerve Sheath Diameter in Predicting the Neurological Outcomes of Cardiac Arrest Survivors: A Systematic Review and Meta-analysis by Parisa Jafari Khouzani, Erfan Rahmani, Mehdi Rezaei, Sasan Pohrbagher Benam, Atousa Moghadam Fard, Reza Amani-Beni, Maziar Daneshvar, Faezeh Jalayer Sarnaghy, Naghme Masoomi Goodarzi, Ramila Abedi Azar, Amirhossein Mirbolook, Peyman Bashghareh, Elham Bibak, Babak Goodarzi, Zahra Salarinezhad, Reza Zahedpasha, Marzieh Hajizaman, Negar Pourhossein Rahmani, Azam Darvishi, Alireza Hadizadeh, Fatemeh Zandi, Ashkan Azizi, Armin Naderi, Sepideh Shah Hosseini, Asie Sanjary, Mozhdeh Mohammadi Virsoudi, Habibollah Afshang, Seyedsaber Mirabdali, Navid Fathalian, Pouria Momeni, Mahsan Valizade, Fateme Nozari, Hamed Ghorbani, Sanam Mohammadzadeh, Seyed Kiavash Sajadi, Azam Abdollahi, Mehrdad Farrokhi

“…However, since the cut-off values and methods of ONSD measurement affect its predictive performance, further studies will be required to standardize these factors to achieve optimal predictive parameters. …”
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Retracted: Predicting the Elastic Modulus of Nanoparticle-Reinforced Polymer Matrix Composites Based on Digital Image Processing and Finite Elements by Advances in Materials Science and Engineering

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PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

Subjects: “…protein structure prediction…”
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Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population by Eun Kyung Choe, Hwanseok Rhee, Seungjae Lee, Eunsoon Shin, Seung-Won Oh, Jong-Eun Lee, Seung Ho Choi

“…We aimed to develop an MS prediction model using genetic and clinical factors of nonobese Koreans through machine learning methods. …”
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Predictive factors of fibrotic interstitial lung abnormality on high-resolution computed tomography scans: a prospective observational study by Kazuya Ichikado, Hidenori Ichiyasu, Kazuhiro Iyonaga, Kodai Kawamura, Yuko Yasuda, Keisuke Anan, Hiroko Okabayashi, Kimitaka Akaike, Noritaka Higashi, Takeshi Johkoh, Kiminori Fujimoto, Tetsuo Saito, Jun Morinaga, Minoru Yoshida, Katsuhiko Mitsuzaki, Takuro Sakagami

“…Therefore, we aimed to examine these clinical characteristics and clarify the predictive factors of fibrotic interstitial lung abnormalities on high-resolution computed tomography scans. …”
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Predictions of Muscle Forces During the Cross-Body Adduction and Hand-Behind-the-Back Tests to Assess Osteoarthritis of the Acromioclavicular Joint by Kamal Gautam, Mohamed Samir Hefzy, Kyle Behrens, Abdul A. Mustapha

“…The results revealed some agreements and significant discrepancies in most muscle force predictions between the OpenSim and AnyBody Modeling System^TM. …”
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Identification of a novel immunogenic cell death-related classifier to predict prognosis and optimize precision treatment in hepatocellular carcinoma by Dongjing Zhang, Bingyun Lu, Qianqian Ma, Wen Xu, Qi Zhang, Zhiqi Xiao, Yuanheng Li, Ren Chen, An-jiang Wang

“…In conclusion, our findings revealed that the ICD score could serve as a robust prognostic biomarker to predict the benefits of immunotherapy and optimize the clinical decision-making of HCC patients.…”
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Retracted: Predicting the Spread of Vessels in Initial Stage Cervical Cancer through Radiomics Strategy Based on Deep Learning Approach by Advances in Materials Science and Engineering

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Multiplex-PCR technique to predict polymorphic antigens – M, N, S and s – and associations between their alleles and Mia-associated hybrid glycophorins by Thanaporn Kerdthip, Oytip Nathalang, Sarisa Chidtrakoon, Tanaporn Choychimplee, Dollapak Apipongrat, Kamphon Intharanut

“…Individuals with the GYPA*M/M and GYPB*s/s genotypes, predicted M + N − S− s + phenotypes, will thus most likely to express the Mi(a+) antigen. …”
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Predicting early diagnosis of intensive care unit-acquired weakness in septic patients using critical ultrasound and biological markers by Ling Lei, Liang He, Tongjuan Zou, Jun Qiu, Yi Li, Ran Zhou, Yao Qin, Wanhong Yin

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Mortality Prediction Using SaO2/FiO2 Ratio Based on eICU Database Analysis by Sharad Patel, Gurkeerat Singh, Samson Zarbiv, Kia Ghiassi, Jean-Sebastien Rachoin

“…We hypothesize that S/F is noninferior to P/F as a predictive feature for ICU mortality. Using a machine-learning approach, we hope to demonstrate the relative mortality predictive capacities of S/F and P/F. …”
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Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor by Bui Thanh Khoa, Tran Trong Huynh

“…The rolling window approach is used in combination with the Root Mean Square Error (RMSE), and the results of the FF5 model with the LSTM-RNN algorithm are more efficient in prediction error than the MLE methodology. This contribution encourages investors and hedge fund managers to use the LSTM-RNN algorithm to boost forecasting efficiency.…”
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Predictive Factors Associated with Inappropriate Intravenous Proton Pump Inhibitors Use in Hospitalized Patients: A Case-Control Study by Niveen Khoury, David Stepensky, Naim Abu Freha, Mahmud Mahamid, Tawfik Khoury, Amir Mari

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Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning by Alireza Hakimi, Parvin Ghafarian

“…Abstract Predicting wind speed simultaneously at multiple heights, particularly at 10 and 100 metres (m), presents unique challenges due to diverse influences. …”
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A radiomics and deep learning nomogram developed and validated for predicting no-collapse survival in patients with osteonecrosis after multiple drilling by Fan Liu, De-bao Zhang, Shi-huan Cheng, Gui-shan Gu

“…Hence, the purpose of the study is to utilize radiomics and deep learning for predicting no-collapse survival in patients with femoral head osteonecrosis. …”
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Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets by Kubra Noor, Ubaida Fatima

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sAMDGCN: sLSTM-Attention-Based Multi-Head Dynamic Graph Convolutional Network for Traffic Flow Forecasting by Shiyuan Zhang, Yanni Ju, Weishan Kong, Hong Qu, Liwei Huang

Subjects: “…traffic flow prediction…”
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