DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Furthermore, this paper presents future directions for future researchers to follow SR trends with potential DL-based algorithms.…”
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A review of machine learning and deep learning for Parkinson’s disease detection by Hajar Rabie, Moulay A. Akhloufi

“…We discuss the preprocessing methods applied, the state-of-the-art models utilized, and their performance. Our evaluation included different algorithms such as support vector machines (SVM), random forests (RF), convolutional neural networks (CNN). …”
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Reproduction of reservoir pressure in oil field development: prospects and problems of using methods machine learning by I. N. Ponomarevа, D. A. Martyushev

“…Three oil deposits of one field with different geological and physical conditions were selected as the object of study. …”
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Prediction of Auditory Performance in Cochlear Implants Using Machine Learning Methods: A Systematic Review by Beyza Demirtaş Yılmaz

“…Study design, machine learning algorithms, and audiological measurements were evaluated in the data analysis. …”
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Study on consistency between liver fat fraction quantification based on photon-counting CT and MRI proton density fat fraction by CAI Xinxin, DENG Rong, XU Xinxin, XU Zhihan, CHANG Rui, DONG Haipeng, LIN Huimin, YAN Fuhua

“…The performance of the adjusted threshold in measuring liver fat content was evaluated in the validation cohort, as well as the consistency across subgroups with different scanning protocols. …”
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A High Resolution Melting Analysis (HRM) PCR assay for the detection and identification of Old World Leishmania species. by Yusr Saadi-Ben Aoun, Hejer Souguir, Hamed Chouaieb, Mongia Kraiem, Insaf Bel Hadj Ali, Ahmed S Chakroun, Florian Noguier, Akila Fathallah-Mili, David Piquemal, Ikram Guizani

“…Its integration into molecular diagnostic algorithms for CL or in eco-epidemiological studies holds promise for improving disease management and control.…”
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A study on the risk prediction model for venous thromboembolism in orthopedic inpatients based on machine learning by Bo Zhang, Yumei Qin, Liandi Jiu, Chunming Qin, Jiangbo Wang, Haiqing Zhao

“…Feature analysis and data mining were conducted, and eight different machine learning algorithms were used to build the prediction model. …”
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CLINICAL AND LABORATORY ASPECTS OF DETECTING SPECIFIC IgE ANTIBODIES TO COW’S MILK AND ITS COMPONENTS by N. A. Alkhutova, N. A. Kovyazina, O. L. Zhizhina

“…An immunochemoluminescent assay of specific IgE antibody levels to the cow milk using IMMULITE 2000/XPi analyzer has revealed its good informative value at different approaches to prediction and evaluation of food allergy treatment, both oriented for a critical cutoff value of 3 МU/L, and by monitoring a decrease in antibody levels. …”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…The spectral data were correlated with the determination of three-component contents using the partial least squares regression (PLSR) method. Then different algorithms, such as competitive adaptive weighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE), and random frog hopping (RF), were used for model simplification and feature selection. …”
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Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis by Ivars Neiders, Signe Mežinska, Neeltje E. M. van Haren

“…In several cases there is no empirical knowledge that determines whether particular concerns are justified (stigmatisation, use of machine learning algorithms).…”
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The multi-omics analysis identifies a novel endoplasmic reticulum stress and immune related genes signature in lung adenocarcinoma by Danhe Huang, Yuying Liu, Mingyu Yuan, Xiongwei Wang, Lianqing Hong

“…Tumor microenvironment characteristics were evaluated using the CIBERSORT and ESTIMATE algorithm. …”
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MRI R2* and quantitative susceptibility mapping in brain tissue with extreme iron overload by Christoph Birkl, Marlene Panzer, Christian Kames, Anna Maria Birkl-Toeglhofer, Alexander Rauscher, Bernhard Glodny, Elke R. Gizewski, Heinz Zoller

“…Our study in patients with aceruloplasminemia revealed that the choice of reference region significantly influences susceptibility values, with variations exceeding algorithm-dependent differences. Key Points R2* and QSM vary across algorithms in brain tissue with iron overload. …”
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NETosis-based prognostic model reveals immune modulation in clear cell renal cell carcinoma using single-cell and bulk RNA sequencing by Zijie Yu, Zihao Xu, Xi Zhang, Wenchuan Shao, Da Zhong, Xinghan Yan, Tingfei Jiang, Yichun Wang, Ninghong Song

“…We developed a prognostic framework for netosis using univariate, Lasso, and multivariate Cox regression analyses. The CIBERSORT algorithm was employed to compute immune infiltration metrics for The Cancer Genome Atlas (TCGA) dataset. …”
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Automatic recognition of adrenal incidentalomas using a two-stage cascade network: a multicenter study by Xiao Xie, Sheng-Xiao Ma, Xiang-De Luo, De-Ying Liao, Dong Han, Zhi-Peng Huang, Zhi-Hua Chen, Xian-Ping Li, Bo Li, Shi-Di Hu, Yan-Jun Chen, Peng-Fei Liu, De-Zhong Zheng, Hui Xia, Cun-Dong Liu, Shan-Chao Zhao, Ming-Kun Chen

“…In the test cohort, the cascade network achieved AUC of more than 80% and accuracy of more than 75% for both left and right adrenal glands.Conclusions The two-stage cascade network based on a deep learning algorithm can be used for automatic recognition of AIs in nonenhanced CT from different centers.…”
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Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal versus Visible Spectrum Video-Based Systems by Ting Fu, Joshua Stipancic, Sohail Zangenehpour, Luis Miranda-Moreno, Nicolas Saunier

“…Retraining the algorithm on thermal data yielded an improvement in the global accuracy of 48%. …”
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Characteristics of postoperative management of patients after microendolaryngeal laser resection of malignant tumor of the voice box by N. A. Daikhes, V. V. Vinogradov, S. S. Reshulskii, R. R. Khabiev, E. B. Fedorova, M. L. Isaeva, S. M. Kochieva, K. V. Mishchenko

“…Cordectomy volume was evaluated in accordance with the classification of the European Laryngological Society (ELS). …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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The Impact of an Adaptive mHealth Intervention on Improving Patient-Provider Health Care Communication: Secondary Analysis of the DIAMANTE Trial by Lynn Leng, Marvyn R Arévalo Avalos, Adrian Aguilera, Courtney R Lyles

“…Our primary analysis used mixed-effects modeling within an intent-to-treat analysis to determine differences in CAHPS scores by trial arm. …”
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Characteristics of postoperative management of patients after microendolaryngeal laser resection of malignant tumor of the voice box by N.  A.  Daikhes, V.  V.  Vinogradov, S.  S.  Reshulskii, R.  R.  Khabiev, E.  B.  Fedorova, M.  L.  Isaeva, S.  M.  Kochieva, K.  V.  Mishchenko

“…Cordectomy volume was evaluated in accordance with the classification of the European Laryngological Society (ELS). …”
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18F-FDG dose reduction using deep learning-based PET reconstruction by Ryuji Akita, Komei Takauchi, Mana Ishibashi, Shota Kondo, Shogo Ono, Kazushi Yokomachi, Yusuke Ochi, Masao Kiguchi, Hidenori Mitani, Yuko Nakamura, Kazuo Awai

“…Abstract Background A deep learning-based image reconstruction (DLR) algorithm that can reduce the statistical noise has been developed for PET/CT imaging. …”
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