Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

“…The fast change from 5G to 6G networks calls for extremely accurate network traffic prediction and effective resource allocation to meet rising data volumes and ultra-low latency requirements. …”
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Super‐Resolution Ultrasound Radiomics Can Predict the Upstaging of Ductal Carcinoma In Situ by Liang Yang, Xiaoxian Li, Zhiyuan Wang, Qian Li, Juan Fu, Xuebin Zou, Xia Liang, Xu Liu, Ruirui Zhang, Junjun Chen, Hui Xie, Yini Huang, Jianhua Zhou

“…However, it is hard to preoperatively predict the upstaging of biopsy‐proven DCIS. This study aims to develop an effective radiomics model for predicting the upstaging of DCIS based on super‐resolution (SR) ultrasound images. …”
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Preoperative prediction of pituitary neuroendocrine tumor invasion using multiparametric MRI radiomics by Qiuyuan Yang, Tengfei Ke, Jialei Wu, Yubo Wang, Jiageng Li, Yimin He, Jianxian Yang, Nan Xu, Bin Yang

“…ObjectiveThe invasiveness of pituitary neuroendocrine tumor is an important basis for formulating individualized treatment plans and improving the prognosis of patients. Radiomics can predict invasiveness preoperatively. To investigate the value of multiparameter magnetic resonance imaging (mpMRI) radiomics in predicting pituitary neuroendocrine tumor invasion into the cavernous sinus (CS) before surgery.Patients and methodsThe clinical data of 133 patients with pituitary neuroendocrine tumor (62 invasive and 71 non-invasive) confirmed by surgery and pathology who underwent preoperative mpMRI examination were retrospectively analyzed. …”
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Prediction of Therapeutic Response and Prognosis in Ovarian Cancer Patients With Plasma Circulating Biomarkers by Haixia Cheng, Guangwen Yuan, Leilei Liang, Tiantian Wang, Jiarun Zhu, Hongying Yang, Zhendiao Zhou, Pei Wang, Qianqian Song, Yuchen Jiao, Mei Liu, Lingying Wu

“…ABSTRACT Background To assess whether changes in TP53 mutations and copy number alterations (CNA) in plasma circulating tumor DNA (ctDNA) can predict treatment response and prognosis in platinum‐resistant recurrent ovarian cancer (PROC) patients. …”
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Identification of cancer-associated fibroblast signature genes for prognostic prediction in colorectal cancer by Wei Jin, Yuchang Lu, Jingen Lu, Zhenyi Wang, Yixin Yan, Biao Liang, Shiwei Qian, Jiachun Ni, Yiheng Yang, Shuo Huang, Changpeng Han, Haojie Yang

“…The expression trends of CD177 and CCDC78 were consistent with our predicted results.ConclusionThe CAFs risk model accurately predicted prognosis, immune cell infiltration, and stromal estimates. …”
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Cuproptosis-related lncRNA predicts prognosis and immune pathways in osteosarcoma patients by LIAO Jun, FENG Yanbin, XI Deshuang, ZONG Shaohui

“…Objective To identify cuproptosis-related lncRNAs (CRLs) and use them to construct models to predict survival in osteosarcoma (OS) patients. Methods RNA-seq data of OS patients were downloaded from the TARGET database along with relevant clinical information. …”
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PREDICTION OF VERTICAL IMPACTION OF LOWER WISDOM TOOTH ACCORDING ORTHOPANTOMOGRAPHY OF LOWER JAW by A.M. Hohol, A.I. Pankevych, I.A. Kolisnyk, D.S. Machulenko, Ya.A. Hohol

“…To substantiate the algorithm for predicting the vertical retention of third lower molar in order to improve treatment tactics for the preservation or removal of the tooth which based on the obtained search data and the results of our own clinical observations and it is planned in the future. …”
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Damage prediction of rear plate in Whipple shields based on machine learning method by Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen

“…The results demonstrate that the training and prediction accuracies using the Random Forest (RF) algorithm significantly surpass those using Artificial Neural Networks (ANNs) and Support Vector Machine (SVM). …”
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Monitoring land-use changes and predicting their spatio-temporal trends in Hamedan City by Naser Shafiei Sabet, Faranak Feyzbabaei cheshmeh sefidi

“…The CA-MARKOV model also identifies how land-use changes in Hamedan and simulates and predicts land use and its changes in 2050.Material and methods: In this study, after obtaining satellite images of TM, ETM, and OLI sensors, preprocessing steps including various radiometric and geometric corrections were performed on the images.Then, the classification of satellite images was done using Google Earth software and the vector support algorithm. …”
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Machine learning and molecular docking prediction of potential inhibitors against dengue virus by George Hanson, Joseph Adams, Daveson I. B. Kepgang, Luke S. Zondagh, Lewis Tem Bueh, Andy Asante, Soham A. Shirolkar, Maureen Kisaakye, Hem Bondarwad, Olaitan I. Awe

“…The detailed interactions, toxicity, stability, and conformational changes of selected compounds were assessed through protein-ligand interaction studies, molecular dynamics (MD) simulations, and binding free energy calculations.ResultsWe implemented a robust three-dataset splitting strategy, employing the Logistic Regression algorithm, which achieved an accuracy of 94%. The model successfully predicted 18 known DENV inhibitors, with 11 identified as active, paving the way for further exploration of 2683 new compounds from the ZINC and EANPDB databases. …”
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Video-fluoroscopic swallowing study scale for predicting aspiration pneumonia in Parkinson's disease. by Satoshi Tomita, Tomoko Oeda, Atsushi Umemura, Masayuki Kohsaka, Kwiyoung Park, Kenji Yamamoto, Hiroshi Sugiyama, Hideyuki Sawada

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Enhancing Smart and Zero-Carbon Cities Through a Hybrid CNN-LSTM Algorithm for Sustainable AI-Driven Solar Power Forecasting (SAI-SPF) by Haytham Elmousalami, Felix Kin Peng Hui, Aljawharah A. Alnaser

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A Nomogram for Predicting Survival in Patients with SARS-CoV-2 Omicron Variant Pneumonia Based on Admission Data by Yang Y, Li D, Nie J, Wang J, Huang H, Hang X

“…Risk analysis was performed using clinical symptoms, laboratory findings, and chest CT imaging features. A predictive algorithm was developed using Cox multivariate analysis.Results: The high-risk group had a shorter survival duration than the low-risk group. …”
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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

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Early prediction of cognitive impairment in adults aged 20 years and older using machine learning and biomarkers of heavy metal exposure by Ali Nabavi, Farimah Safari, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Hossein Molavi Vardanjani

“…Machine learning can integrate multi-factorial data to predict cognitive outcomes. Objective: To develop and validate machine learning models for early prediction of cognitive impairment risk using demographics, clinical factors, and biomarkers of heavy metal exposure. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…By establishing a multi-level classification framework that included traditional statistical models (such as ARIMA), ML models (such as SVM), deep learning (DL) models (such as CNN, LSTM), ensemble learning methods (such as AdaBoost), and hybrid models (such as the fusion architecture of intelligent optimization algorithms and neural networks), it revealed that the hybrid modelling strategy effectively improved the prediction accuracy of the model through feature combination optimization and model cascade integration. …”
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Identifying leptospirosis hotspots in Selangor: uncovering climatic connections using remote sensing and developing a predictive model by Muhammad Akram Ab Kadir, Rosliza Abdul Manaf, Siti Aisah Mokhtar, Luthffi Idzhar Ismail

“…Conclusions This GIS-based study identified a primarily sporadic occurrence of leptospirosis in Selangor with minimal spatial clustering. The LGBM algorithm effectively predicted leptospirosis hotspots based on the analysed hydroclimatic factors. …”
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Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study by Sanghwan Kim, Sowon Jang, Borham Kim, Leonard Sunwoo, Seok Kim, Jin-Haeng Chung, Sejin Nam, Hyeongmin Cho, Donghyoung Lee, Keehyuck Lee, Sooyoung Yoo

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Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

“…Consequently, Emperor Penguins Colony (EPC) optimization algorithm was also employed for selecting the essential features, which reduces the data dimensionality and assists the predictive algorithm to focus on important features in its training phase. …”
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Risk Factors and Predictive Model for Ischemic Complications in Endovascular Treatment of Intracranial Aneurysms: Insights From a Large Patient Cohort by Jianwen Jia, Zeping Jin, Mirzat Turhon, Yixin Lin, Xinjian Yang, Yang Wang, Yunpeng Liu

“…Our study aimed to identify the risk factors for ischemic complications after the interventional treatment of IAs and to make an individualized prediction of the occurrence of ischemic complications, providing important reference guidance for clinicians. …”
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