Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy by Li Yucheng, Qiu Lingyun, Shao Kainan, Jia Yongshi, Zhan Wenming, Ding Jieni, Chen Weijun

“…The test results were compared with the contouring results of commercial automatic contouring software based on the deep learning (DL) algorithm model. …”
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Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers by Junxiao Wang, Shiying Zhang, Jia Li, Mei Deng, Zhi Zeng, Zehua Dong, Fangfang Chen, Wen Liu, Lianlian Wu, Honggang Yu

“…The Ki-67 proliferation index was quantitatively assessed using digital image analysis. …”
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Phase I Pharmacokinetics Study of Drug «COVID-globulin» (Specific Human Immunoglobulin Against COVID-19) by T. I. Smolyanova, N. S. Bagaeva, M. A. Kolganova, I. E. Shohin, A. M. Nikolaeva, T. V. Vyaznikova, A. A. Pankratova, E. A. Bykova

“…The clinical and analytical stages of the study of the pharmacokinetics of drug "COVID-globulin", as well as the analysis of the safety and parameters of pharmacokinetics were carried as part of a clinical study of the safety, tolerability and pharmacokinetics of the drug immunoglobulin ("COVID-globulin"), not less than 160 anti-COVID units/mL (ACU/mL), JSC "NPO Microgen", owner of the registration certificate of JSC "Natsibio", Russia. Quantitative determination of antibody concentrations against SARS-CoV-2 was carried out by enzyme-linked immunosorbent assay using spectrophotometric detection in the visible range of the spectrum on an automatic plate enzyme-linked immunosorbent assay analyzer Lazurite (Dynex Technologies Inc., USA). …”
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Three-stage registration pipeline for dynamic lung field of chest X-ray images based on convolutional neural networks by Yingjian Yang, Jie Zheng, Peng Guo, Qi Gao, Yingwei Guo, Ziran Chen, Chengcheng Liu, Tianqi Wu, Zhanglei Ouyang, Huai Chen, Yan Kang, Yan Kang, Yan Kang

“…Nevertheless, accurate lung field registration results may be more favored and exciting than the registration results of the entire CXR images and hold promise for dynamic lung field analysis in clinical practice.ObjectiveBased on the above, a registration model of the dynamic lung field of CXR images based on AC-RegNet and static CXR images is urgently developed to register these dynamic lung fields for clinical quantitative analysis.MethodsThis paper proposes a fully automatic three-stage registration pipeline for the dynamic lung field of CXR images. …”
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Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks. by Petros-Pavlos Ypsilantis, Musib Siddique, Hyon-Mok Sohn, Andrew Davies, Gary Cook, Vicky Goh, Giovanni Montana

“…We take a "radiomics" approach whereby a large amount of quantitative features is automatically extracted from pretherapy PET images in order to build a comprehensive quantification of the tumor phenotype. …”
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Real-world assessment of healthcare provided by the National Health Service: The network of regional Beaver research platforms by Federico Rea, Pietro Pugni, Dario Pescini, Luigi Palmieri, Simona Giampaoli, Flavia Carle, Giovanni Corrao

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Combining Deep Learning and Street View Images for Urban Building Color Research by Wenjing Li, Qian Ma, Zhiyong Lin

“…The framework is composed of two phases: “deep learning” and “quantitative analysis.” In the “deep learning” phase, a deep convolutional neural network (DCNN)-based color extraction model is designed to automatically learn building color information from street view images; in the “quantitative analysis” phase, building color is quantitatively analyzed at the overall and local levels, and a color clustering model is designed to quantitatively display the color relationship to comprehensively understand the current status of urban building color. …”
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A synthesis method for zero-sum mean-payoff asynchronous probabilistic games by Wei Zhao, Wanwei Liu, Zhiming Liu, Tiexin Wang

“…There is also a class of synthesis problems aiming at quantitative properties, such as mean-payoff values, and this type of problem is called a quantitative problem. …”
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Computer Vision-Based Adhesion Quality Inspection Model for Exterior Insulation and Finishing System by Mingyun Kang, Sebeen Yoon, Taehoon Kim

“…Thus, this study proposes a CV-based automatic adhesion quality-inspection model for EIFS that can quickly and quantitatively inspect the shape and amount of adhesive. …”
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ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile by WANG Zhengyan, CHEN Meng, YANG Guofeng, LIU Guoquan, PEI Yang, CHEN Qiang

“…Transit times were obtained via automatic peak fitting, enabling the quantitative calculation of CO2 flow in different spaces of the complex string structure. …”
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DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge by Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew, Alexandre Hutton, Roland Wiest, Johannes Kaesmacher, Uta Hanning, Arsany Hakim, Richard Zubal, Waldo Valenzuela, David Robben, Diana M. Sima, Vincenzo Anania, Arne Brys, James A. Meakin, Anne Mickan, Gabriel Broocks, Christian Heitkamp, Shengbo Gao, Kongming Liang, Ziji Zhang, Md Mahfuzur Rahman Siddiquee, Andriy Myronenko, Pooya Ashtari, Sabine Van Huffel, Hyunsu Jeong, Chiho Yoon, Chulhong Kim, Jiayu Huo, Sebastien Ourselin, Rachel Sparks, Albert Clèrigues, Arnau Oliver, Xavier Lladó, Liam Chalcroft, Ioannis Pappas, Jeroen Bertels, Ewout Heylen, Juliette Moreau, Nima Hatami, Carole Frindel, Abdul Qayyum, Moona Mazher, Domenec Puig, Shao-Chieh Lin, Chun-Jung Juan, Tianxi Hu, Lyndon Boone, Maged Goubran, Yi-Jui Liu, Susanne Wegener, Florian Kofler, Ivan Ezhov, Suprosanna Shit, Moritz R. Hernandez Petzsche, Michael Müller, Bjoern Menze, Jan S. Kirschke, Benedikt Wiestler

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Multitemporal Volume Registration for the Analysis of Rheumatoid Arthritis Evolution in the Wrist by Roberta Ferretti, Silvana G. Dellepiane

“…This paper describes a method based on an automatic segmentation process to coregister carpal bones of the same patient imaged at different time points. …”
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Risk stratification in neuroblastoma patients through machine learning in the multicenter PRIMAGE cohort by Jose Lozano-Montoya, Ana Jimenez-Pastor, Almudena Fuster-Matanzo, Glen J. Weiss, Leonor Cerda-Alberich, Diana Veiga-Canuto, Blanca Martínez-de-Las-Heras, Blanca Martínez-de-Las-Heras, Adela Cañete-Nieto, Sabine Taschner-Mandl, Barbara Hero, Thorsten Simon, Ruth Ladenstein, Luis Marti-Bonmati, Luis Marti-Bonmati, Angel Alberich-Bayarri

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Synthetic ECG signal generation using generative neural networks. by Edmond Adib, Fatemeh Afghah, John J Prevost

“…Therefore, there is always a need for more ECG data, especially for the training of automatic diagnosis machine learning models, which perform better when trained on a balanced dataset. …”
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A fully automated machine-learning-based workflow for radiation treatment planning in prostate cancer by Jan-Hendrik Bolten, David Neugebauer, Christoph Grott, Fabian Weykamp, Jonas Ristau, Stephan Mende, Elisabetta Sandrini, Eva Meixner, Victoria Navarro Aznar, Eric Tonndorf-Martini, Kai Schubert, Christiane Steidel, Lars Wessel, Jürgen Debus, Jakob Liermann

“…Results: The automatic deep-learning segmentation of the target volume revealed a close agreement between the deep-learning based and expert contours referring to Dice Similarity- and Hausdorff index. …”
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Extraction of the essential elements for urban systems modelling – A word-to-vector approach by Tatenda Hatidani Katsumbe, Arnesh Telukdarie, Megashnee Munsamy, Christian Tshukudu

“…In order to resolve these complexities, this study seeks a systems-based approach including a 2-tier structured protocol, leveraging qualitative-to-quantitative techniques to automatically extract the key systems which impact the development of city models. …”
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Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images. by Ulas Bagci, Jianhua Yao, Kirsten Miller-Jaster, Xinjian Chen, Daniel J Mollura

“…The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. …”
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches. by Paolo Belardinelli, Erick Ortiz, Gareth Barnes, Uta Noppeney, Hubert Preissl

“…A Bayesian approach to the Minimum Norm Model (MNM), an Empirical Bayesian Beamformer (EBB) and two iterative Bayesian schemes (Automatic Relevance Determination (ARD) and Greedy Search (GS)) are quantitatively compared. …”
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Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data by Guocheng Qin, Yin Zhou, Kaixin Hu, Daguang Han, Chunli Ying

“…This paper proposes a fully automatic method of reconstructing parameterized BIM by using point clouds to address the abovementioned problems. …”
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A survey of MRI-based brain tissue segmentation using deep learning by Liang Wu, Shirui Wang, Jun Liu, Lixia Hou, Na Li, Fei Su, Xi Yang, Weizhao Lu, Jianfeng Qiu, Ming Zhang, Li Song

“…It includes the performance and quantitative analysis of the state-of-the-art methods. …”
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