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7,117 results on '"Li, Hongwei"'

218. Author Correction: Federated learning enables big data for rare cancer boundary detection

Author

Pati, Sarthak, Baid, Ujjwal, Edwards, Brandon, Sheller, Micah, Wang, Shih-Han, Reina, G. Anthony, Foley, Patrick, Gruzdev, Alexey, Karkada, Deepthi, Davatzikos, Christos, Sako, Chiharu, Ghodasara, Satyam, Bilello, Michel, Mohan, Suyash, Vollmuth, Philipp, Brugnara, Gianluca, Preetha, Chandrakanth J., Sahm, Felix, Maier-Hein, Klaus, Zenk, Maximilian, Bendszus, Martin, Wick, Wolfgang, Calabrese, Evan, Rudie, Jeffrey, Villanueva-Meyer, Javier, Cha, Soonmee, Ingalhalikar, Madhura, Jadhav, Manali, Pandey, Umang, Saini, Jitender, Garrett, John, Larson, Matthew, Jeraj, Robert, Currie, Stuart, Frood, Russell, Fatania, Kavi, Huang, Raymond Y., Chang, Ken, Balaña, Carmen, Capellades, Jaume, Puig, Josep, Trenkler, Johannes, Pichler, Josef, Necker, Georg, Haunschmidt, Andreas, Meckel, Stephan, Shukla, Gaurav, Liem, Spencer, Alexander, Gregory S., Lombardo, Joseph, Palmer, Joshua D., Flanders, Adam E., Dicker, Adam P., Sair, Haris I., Jones, Craig K., Venkataraman, Archana, Jiang, Meirui, So, Tiffany Y., Chen, Cheng, Heng, Pheng Ann, Dou, Qi, Kozubek, Michal, Lux, Filip, Michálek, Jan, Matula, Petr, Keřkovský, Miloš, Kopřivová, Tereza, Dostál, Marek, Vybíhal, Václav, Vogelbaum, Michael A., Mitchell, J. Ross, Farinhas, Joaquim, Maldjian, Joseph A., Yogananda, Chandan Ganesh Bangalore, Pinho, Marco C., Reddy, Divya, Holcomb, James, Wagner, Benjamin C., Ellingson, Benjamin M., Cloughesy, Timothy F., Raymond, Catalina, Oughourlian, Talia, Hagiwara, Akifumi, Wang, Chencai, To, Minh-Son, Bhardwaj, Sargam, Chong, Chee, Agzarian, Marc, Falcão, Alexandre Xavier, Martins, Samuel B., Teixeira, Bernardo C. A., Sprenger, Flávia, Menotti, David, Lucio, Diego R., LaMontagne, Pamela, Marcus, Daniel, Wiestler, Benedikt, Kofler, Florian, Ezhov, Ivan, Metz, Marie, Jain, Rajan, Lee, Matthew, Lui, Yvonne W., McKinley, Richard, Slotboom, Johannes, Radojewski, Piotr, Meier, Raphael, Wiest, Roland, Murcia, Derrick, Fu, Eric, Haas, Rourke, Thompson, John, Ormond, David Ryan, Badve, Chaitra, Sloan, Andrew E., Vadmal, Vachan, Waite, Kristin, Colen, Rivka R., Pei, Linmin, Ak, Murat, Srinivasan, Ashok, Bapuraj, J. Rajiv, Rao, Arvind, Wang, Nicholas, Yoshiaki, Ota, Moritani, Toshio, Turk, Sevcan, Lee, Joonsang, Prabhudesai, Snehal, Morón, Fanny, Mandel, Jacob, Kamnitsas, Konstantinos, Glocker, Ben, Dixon, Luke V. M., Williams, Matthew, Zampakis, Peter, Panagiotopoulos, Vasileios, Tsiganos, Panagiotis, Alexiou, Sotiris, Haliassos, Ilias, Zacharaki, Evangelia I., Moustakas, Konstantinos, Kalogeropoulou, Christina, Kardamakis, Dimitrios M., Choi, Yoon Seong, Lee, Seung-Koo, Chang, Jong Hee, Ahn, Sung Soo, Luo, Bing, Poisson, Laila, Wen, Ning, Tiwari, Pallavi, Verma, Ruchika, Bareja, Rohan, Yadav, Ipsa, Chen, Jonathan, Kumar, Neeraj, Smits, Marion, van der Voort, Sebastian R., Alafandi, Ahmed, Incekara, Fatih, Wijnenga, Maarten M. J., Kapsas, Georgios, Gahrmann, Renske, Schouten, Joost W., Dubbink, Hendrikus J., Vincent, Arnaud J. P. E., van den Bent, Martin J., French, Pim J., Klein, Stefan, Yuan, Yading, Sharma, Sonam, Tseng, Tzu-Chi, Adabi, Saba, Niclou, Simone P., Keunen, Olivier, Hau, Ann-Christin, Vallières, Martin, Fortin, David, Lepage, Martin, Landman, Bennett, Ramadass, Karthik, Xu, Kaiwen, Chotai, Silky, Chambless, Lola B., Mistry, Akshitkumar, Thompson, Reid C., Gusev, Yuriy, Bhuvaneshwar, Krithika, Sayah, Anousheh, Bencheqroun, Camelia, Belouali, Anas, Madhavan, Subha, Booth, Thomas C., Chelliah, Alysha, Modat, Marc, Shuaib, Haris, Dragos, Carmen, Abayazeed, Aly, Kolodziej, Kenneth, Hill, Michael, Abbassy, Ahmed, Gamal, Shady, Mekhaimar, Mahmoud, Qayati, Mohamed, Reyes, Mauricio, Park, Ji Eun, Yun, Jihye, Kim, Ho Sung, Mahajan, Abhishek, Muzi, Mark, Benson, Sean, Beets-Tan, Regina G. H., Teuwen, Jonas, Herrera-Trujillo, Alejandro, Trujillo, Maria, Escobar, William, Abello, Ana, Bernal, Jose, Gómez, Jhon, Choi, Joseph, Baek, Stephen, Kim, Yusung, Ismael, Heba, Allen, Bryan, Buatti, John M., Kotrotsou, Aikaterini, Li, Hongwei, Weiss, Tobias, Weller, Michael, Bink, Andrea, Pouymayou, Bertrand, Shaykh, Hassan F., Saltz, Joel, Prasanna, Prateek, Shrestha, Sampurna, Mani, Kartik M., Payne, David, Kurc, Tahsin, Pelaez, Enrique, Franco-Maldonado, Heydy, Loayza, Francis, Quevedo, Sebastian, Guevara, Pamela, Torche, Esteban, Mendoza, Cristobal, Vera, Franco, Ríos, Elvis, López, Eduardo, Velastin, Sergio A., Ogbole, Godwin, Soneye, Mayowa, Oyekunle, Dotun, Odafe-Oyibotha, Olubunmi, Osobu, Babatunde, Shu’aibu, Mustapha, Dorcas, Adeleye, Dako, Farouk, Simpson, Amber L., Hamghalam, Mohammad, Peoples, Jacob J., Hu, Ricky, Tran, Anh, Cutler, Danielle, Moraes, Fabio Y., Boss, Michael A., Gimpel, James, Veettil, Deepak Kattil, Schmidt, Kendall, Bialecki, Brian, Marella, Sailaja, Price, Cynthia, Cimino, Lisa, Apgar, Charles, Shah, Prashant, Menze, Bjoern, Barnholtz-Sloan, Jill S., Martin, Jason, and Bakas, Spyridon

Published
2023
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221. The Predictive Value of CHA2DS2-VASc Score on Major Adverse Cardiovascular Events in Patients with Three Vessels or Left Main Diseases of Coronary Heart Disease

Author

WANG Qiushi, LI Hongwei

Subjects
coronary artery disease, cha2ds2-vasc score, syntax score, triple-vessel diseases, left main disease, predictive value, Medicine
Abstract

Background SYNTAX score is the most common system for predicting the prognosis of patients with coronary heart disease based on coronary anatomy and lesions, and an evaluation method based on general clinical data is needed to improve the effectiveness of prediction. Objective To investigate the relationship between CHA2DS2-VASc scores and major adverse cardiovascular events in patients with three-vessel disease (TVD) or left main coronary artery disease (LMD) . Methods A total of 630 TVD/LMD patients were enrolled, and 276 patients were divided into the mild lesion group (0—22 points), 249 cases in the moderate lesion group (23—32 points) and 105 cases in the severe lesion group (≥33 points) according to SYNTAX score. Pearson correlation analysis and partial correlation analysis were used to explore the correlation between quantitative data, and univariate and multivariate Logistic regression analysis were used to investigate whether CHA2DS2-VASc and SYNTAX scores were risk factors for the incidence of MACEs within 3 years. The receiver operating characteristic (ROC) curve was plotted to evaluate the CHA2DS2-VASc score in predicting the occurrence of MACEs within 3 years. The ROC curves for predicting MACEs of CHA2DS2-VASc score, SYNTAX score, and the combination of the two scoring systems were compared using the Delong method. Results There were statistically significant differences in age, congestive heart failure, eGFR, LVEF, SYNTAX score, CHA2DS2-VASc score, MACEs within 3 years, death and non-fatal myocardial infarction among the groups with diferent degree of coronary stenosis (P

Published
2023
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222. Study on altered functional and effective connectivity of bilateral precuneus in drug-naïve first-episode patients with adolescent-onset schizophrenia

Author

Yao Hongchao, Wu Junlin, Li Hongwei, Zhuo Lihua, Huang Guoping, Feng Ruohan, Liu Ruishan, Wang Lu, and Li Zhenlin

Subjects
adolescent, schizophrenia, precuneus, mri, resting state, Psychology, BF1-990, Psychiatry, RC435-571
Abstract

BackgroundCompared with adult-onset schizophrenia， patients with adolescent-onset schizophrenia experience a high genetic susceptibility， severe negative symptoms， high recurrence rate， poor prognosis and social function recovery. And clarifying the brain functional alterations in adolescent-onset schizophrenia is of great significance for further elucidating the pathogenesis of the disease and exploring personalized and precise treatment.ObjectiveTo investigate the altered functional and effective connectivity of bilateral precuneus in first-episode patients with adolescent-onset schizophrenia based on resting-state functional magnetic resonance imaging （rs-fMRI）， thus providing reliable imaging evidence in guiding the study on mechanism involved in adolescent-onset schizophrenia.MethodsTwenty-one drugnaïve first-episode patients with adolescent-onset schizophrenia who met the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） criteria for schizophrenia were enrolled， and another 21 psychiatrially healthy controls matched on age， educational background and gender were concurrently selected. The schizophrenic subjects were evaluated using the Psychotic Symptom Rating Scales （PSYRATS） and Positive and Negative Symptom Scale （PANSS）. All participants underwent rs-fMRI scans， and the whole-brain seed-based functional and effective connectivity analyses were conducted in bilateral cuneus region. Then the correlation between functional connectivity strength and clinical symptoms of patients was discussed.ResultsIn terms of functional connectivity， the functional connectivity of bilateral precuneus and left middle temporal gyrus was increased in patient group compared with healthy control group ［P

Published
2023
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223. Process and Performance Comparison of Iron Coatings by Cold Spraying and Arc Spraying

Author

CAO Dahua, WAN Peng, ZHOU Yujie, YANG Ling, LI Hongwei

Subjects
magnetic permeability, cold spraying, arc spraying, aluminum cookware, iron coating, cross-sectional bonding layer, bonding strength, corrosion resistance, electromagnetic performance change rate, Materials of engineering and construction. Mechanics of materials, TA401-492, Technology
Abstract

A detailed study and analysis were conducted on the preparation conditions and coating properties of two processes of cold spraying and arc spraying for spraying magnetic conductive coatings on the surface of aluminum cookware， providing a basis for the application of highperformance magnetic conductive coatings on the surface of aluminum cookware.By means of scanning electron microscope， tensile testing machine， salt spray test chamber and thermal shock chamber， the cross-sectional morphology， composition， bonding strength， corrosion resistance， cold and hot impact resistance， and electromagnetic performance change rate of coatings prepared by two different processes were studied.Results showed that the prepared coatings both had good electromagnetic heating performance.The magnetic conductive coating prepared by cold spraying was significantly better than that prepared by traditional arc spraying in terms of bonding strength， corrosion resistance and cold and hot impact resistance.The change rate of electromagnetic properties of the magnetic conductive coating prepared by cold spraying was significantly lower than that prepared by traditional arc spraying.However， the noise in service of iron coating with arc spraying was slightly lower than that prepared by cold spraying.

Published
2023
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249. scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

Author

Qian, Kun, Fu, Shiwei, Li, Hongwei, and Li, Wei Vivian

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Generic health relevance, Algorithms, Gene Expression, Gene Expression Profiling, Sequence Analysis, RNA, Single-Cell Analysis, Exome Sequencing, Environmental Sciences, Information and Computing Sciences, Bioinformatics
Abstract

The increasing number of scRNA-seq data emphasizes the need for integrative analysis to interpret similarities and differences between single-cell samples. Although different batch effect removal methods have been developed, none are suitable for heterogeneous single-cell samples coming from multiple biological conditions. We propose a method, scINSIGHT, to learn coordinated gene expression patterns that are common among, or specific to, different biological conditions, and identify cellular identities and processes across single-cell samples. We compare scINSIGHT with state-of-the-art methods using simulated and real data, which demonstrate its improved performance. Our results show the applicability of scINSIGHT in diverse biomedical and clinical problems.

Published
2022

250. METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy

Author

Horvath, Izabela, Paetzold, Johannes C., Schoppe, Oliver, Al-Maskari, Rami, Ezhov, Ivan, Shit, Suprosanna, Li, Hongwei, Ertuerk, Ali, and Menze, Bjoern H.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Novel multimodal imaging methods are capable of generating extensive, super high resolution datasets for preclinical research. Yet, a massive lack of annotations prevents the broad use of deep learning to analyze such data. So far, existing generative models fail to mitigate this problem because of frequent labeling errors. In this paper, we introduce a novel generative method which leverages real anatomical information to generate realistic image-label pairs of tumours. We construct a dual-pathway generator, for the anatomical image and label, trained in a cycle-consistent setup, constrained by an independent, pretrained segmentor. The generated images yield significant quantitative improvement compared to existing methods. To validate the quality of synthesis, we train segmentation networks on a dataset augmented with the synthetic data, substantially improving the segmentation over baseline.

Published
2021

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