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332 results on '"Hammad, Mahmoud"'

1. Management of children and adolescents with chronic myeloid leukemia in chronic phase: International pediatric chronic myeloid leukemia expert panel recommendations: CHRONIC MYELOGENOUS LEUKEMIA

Author

Millot, Frédéric, Ampatzidou, Mirella, Moulik, Nirmalya Roy, Tewari, Sanjay, Elhaddad, Alaa, Hammad, Mahmoud, Pichler, Herbert, Lion, Thomas, Tragiannidis, Athanasios, Shima, Haruko, An, Wenbin, Yang, Wenyu, Karow, Axel, Farah, Roula, Luesink, Maaike, Dworzak, Michael, Sembill, Stephanie, De Moerloose, Barbara, Sedlacek, Petr, Schultz, Kirk R., Kalwak, Krzysztof, Versluys, Birgitta, Athale, Uma, Hijiya, Nobuko, Metzler, Markus, and Suttorp, Meinolf

Published
2025
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2. LNK/SH2B3 as a novel driver in juvenile myelomonocytic leukemia

Author

Wintering, Astrid, Hecht, Anna, Meyer, Julia, Wong, Eric B, Hübner, Juwita, Abelson, Sydney, Feldman, Kira, Kennedy, Vanessa E, Peretz, Cheryl AC, French, Deborah L, Maguire, Jean Ann, Jobaliya, Chintan, Vasquez, Marta Rojas, Desai, Sunil, Dulman, Robin, Nemecek, Eneida, Haines, Hilary, Hammad, Mahmoud, El Haddad, Alaa, Kogan, Scott C, Abdullaev, Zied, Chehab, Farid F, Tasian, Sarah K, Smith, Catherine C, Loh, Mignon L, and Stieglitz, Elliot

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Cancer, Childhood Leukemia, Hematology, Pediatric Cancer, Stem Cell Research - Nonembryonic - Human, Stem Cell Research - Nonembryonic - Non-Human, Genetics, Pediatric, Stem Cell Research, Stem Cell Research - Induced Pluripotent Stem Cell, Rare Diseases, 2.1 Biological and endogenous factors, Humans, Leukemia, Myelomonocytic, Juvenile, Adaptor Proteins, Signal Transducing, Male, Female, Infant, Child, Preschool, Mutation, Intracellular Signaling Peptides and Proteins, Child, Signal Transduction, Pyrazoles, Nitriles, Pyrimidines, Immunology
Abstract

Mutations in five canonical Ras pathway genes (NF1, NRAS, KRAS, PTPN11 and CBL) are detected in nearly 90% of patients with juvenile myelomonocytic leukemia (JMML), a frequently fatal malignant neoplasm of early childhood. In this report, we describe seven patients diagnosed with SH2B3-mutated JMML, including five patients who were found to have initiating, loss-of-function mutations in the gene. SH2B3 encodes the adaptor protein LNK, a negative regulator of normal hematopoiesis upstream of the Ras pathway. These mutations were identified to be germline, somatic or a combination of both. Loss of function of LNK, which has been observed in other myeloid malignancies, results in abnormal proliferation of hematopoietic cells due to cytokine hypersensitivity and activation of the JAK/STAT signaling pathway. In vitro studies of induced pluripotent stem cell-derived JMML-like hematopoietic progenitor cells also demonstrated sensitivity of SH2B3-mutated hematopoietic progenitor cells to JAK inhibition. Lastly, we describe two patients with JMML and SH2B3 mutations who were treated with the JAK1/2 inhibitor ruxolitinib. This report expands the spectrum of initiating mutations in JMML and raises the possibility of targeting the JAK/STAT pathway in patients with SH2B3 mutations.

Published
2024

9. KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT

Author

Tawalbeh, Saja Khaled, Hammad, Mahmoud, and AL-Smadi, Mohammad

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

This research presents our team KEIS@JUST participation at SemEval-2020 Task 12 which represents shared task on multilingual offensive language. We participated in all the provided languages for all subtasks except sub-task-A for the English language. Two main approaches have been developed the first is performed to tackle both languages Arabic and English, a weighted ensemble consists of Bi-GRU and CNN followed by Gaussian noise and global pooling layer multiplied by weights to improve the overall performance. The second is performed for other languages, a transfer learning from BERT beside the recurrent neural networks such as Bi-LSTM and Bi-GRU followed by a global average pooling layer. Word embedding and contextual embedding have been used as features, moreover, data augmentation has been used only for the Arabic language., Comment: 8 pages without references, 4 figures, SemEval 2020 conference

Published
2020

13. Sustainable Heritage Preservation Methodologies Adopted at Al-Baha Region in Saudi Arabia.

Author

MOHAMED HAMMAD, Mahmoud Tarek

Subjects
HISTORIC sites, SUSTAINABLE development, SOCIAL development, DEMOLITION, CIVILIZATION
Abstract

Due to the negative impact of civilization on the local community in the Kingdom of Saudi Arabia, the urban heritage sites of the Kingdom have been subjected to numerous demolition and extinction operations. Recently, the concept of urban preservation has evolved beyond simply restoring and improving heritage sites to encompass preserving heritage within the framework of sustainable development. This approach promotes a long-term balance between protecting the environment and achieving economic and social development. This research aims to evaluate the preservation methodologies and policies applied in three significant case studies in the city of Al-Baha in the Kingdom of Saudi Arabia. The criteria will assess their success in recovering their positive aspects. These three local case studies provide compelling evidence that sustainable development aspects are crucial in advancing toward successful heritage preservation goals. The research employs an inductive methodology to evaluate valuable heritage preservation aspects and propose measures that can be implemented in preservation projects across various regions of Saudi Arabia. In conclusion, the research offers several recommendations that consider promising and appropriate conservation management policies that can be applied in similar projects within the Kingdom of Saudi Arabia. [ABSTRACT FROM AUTHOR]

Published
2025
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16. Global characteristics and outcomes of SARS-CoV-2 infection in children and adolescents with cancer (GRCCC): a cohort study

Author

Ribelles, A Juan, Balduzzi, Adriana, Elhaddad, Alaa, Casanovas, Alejandra, Garcia Velazquez, Alejandra, Laptsevich, Aliaksandra, Chang, Alicia, F. Sampaio, Alessandra Lamenha, González Prieto, Almudena, Lassaletta, Alvaro, Suarez M, Amaranto, Alcasabas, Ana Patricia, Colita, Anca, Morales La Madrid, Andres, Samudio, Angélica, Tondo, Annalisa, Colombini, Antonella, Kattamis, Antonis, Lopez Facundo, N Araceli, Bhattacharyya, Arpita, Alimi, Aurélia, Phulpin, Aurélie, Vakrmanova, Barbora, Aksoy, Basak A, Brethon, Benoit, Kobuin, Jator Brian, Nolasco Monteiro, Carla, Paillard, Catherine, Vezina, Catherine, Ceyhun, Bozkurt, Hentea, Cristiana, Meazza, Cristina, Ortiz-Morales, Daniel, Solorzano, Roque Daniel, Arce Cabrera, Daniela, Zama, Daniele, Ghosh, Debjani, Ramírez-Rivera, Diana, Calle Jara, Doris A, Janic, Dragana, Rey Helo, Elianneth, Gouache, Elodie, Guerrero Quiroz, Enmanuel, Lopez, Enrique, Thebault, Eric, Maradiegue, Essy, de Berranger, Eva, Ebeid, Fatma S E, Galaverna, Federica, Antillon-Klussmann, Federico, Espinoza Chacur, Felipe, Negro, Fernando Daniel, Carraro, Francesca, Compagno, Francesca, Barriga, Francisco, Tamayo Pedraza, Gabriela, Sanchez Fernandez, Gissela, Naidu, Gita, Tokuc, Gülnur, Alias, Hamidah, B Segocio, Hannah Grace, Boudiaf, Houda, Asetre Luna, Imelda, Maia, Iris, Astigarraga, Itziar, Maza, Ivan, Montoya Vásquez, Jacqueline E, Jazbec, Janez, Lazic, Jelena, Beck Dean, Jeniffer, Rouger-Gaudichon, Jeremie, Contreras González, Johanny Carolina, Huerta Aragonés, Jorge, Fuster, José L, Quintana, Juan, Palma, Julia, Svojgr, Karel, Quintero, Karina, Malic Tudor, Karolina, Georgantzi, Kleopatra, P Schultz, Kris Ann, Ureña Horno, Laura, Fraquelli, Lidia, Meneghello, Linda, Shalaby, Lobna, Macias Mora, Lola L, A Renner, Lorna, Nunes Silva, Luciana, Sisinni, Luisa, Hammad, Mahmoud, Fernández Sanmartín, M, Zubieta A, C Marcela, Drozdowski, María Constanza, Kourti, Maria, Palladino, Marcela María, Miranda Madrazo, Maria R, Poiree, Marilyne, Popova, Marina, Melgar, Mario, Baragaño, Marta, Avilés-Robles, Martha J, Provenzi, Massimo, Mendes Lins, Mecneide, Fatih Orhan, Mehmet, Villarroel, Milena, Jerónimo, Mónica, Varas Palma, Mónica, Rafie Raza, Muhammad, M Justin, Mulindwa, Shaheen, Najma, Domínguez-Pinilla, Nerea, Whipple, Nicholas S, André, Nicolas, Hrusak, Ondrej, Velasco Puyó, Pablo, Zacasa Vargas, Pamela, Olate Mellado, Paola, Yola Gassant, Pascale, Diaz Romero, Paulina, De Santis, Raffaella, Kebudi, Rejin, Boranbayeva, Riza, Vasquez, Roberto, Segura, Romel A., Rosado, Roy Enrique, Gómez, Sandra, Raimbault, Sandra, Gunasekera, Sanjeeva, Makkeyah, Sara M, Buyukkapu Bay, Sema, M Gómez, Sergio, Bouttefroy, Séverine, Islam, Shahnoor, Abouelnaga, Sherif, Torres, Silvio Fabio, Cesaro, Simone, Nunes, Sofia, Rouxinol, Soraia, Bhaumik, Sucharita, Saliyeva, Symbat, Inostroza, Tamara, Velasquez, Thelma, Hnin, Tint Myo, Norén-Nyström, Ulrika, Baretta, Valentina, Jimenez-Antolinez, Yajaira Valentine, Pérez Alonso, Vanesa, Ayer Miller, Vanessa, Gandemer, Virginie, Lotero, Viviana, Mishkova, Volha, Gómez-García, Wendy, Margaryan, Yeva, Syed, Yumna, Mukkada, Sheena, Bhakta, Nickhill, Chantada, Guillermo L, Chen, Yichen, Vedaraju, Yuvanesh, Faughnan, Lane, Homsi, Maysam R, Muniz-Talavera, Hilmarie, Ranadive, Radhikesh, Metzger, Monika, Friedrich, Paola, Agulnik, Asya, Jeha, Sima, Lam, Catherine, Dalvi, Rashmi, Hessissen, Laila, Moreira, Daniel C, Santana, Victor M, Sullivan, Michael, Bouffet, Eric, Caniza, Miguela A, Devidas, Meenakshi, Pritchard-Jones, Kathy, and Rodriguez-Galindo, Carlos

Published
2021
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17. SARS-CoV-2 genome variations and evolution patterns in Egypt: a multi-center study

Author

Jalal, Deena, Elzayat, Mariam G., El-Shqanqery, Hend E., Diab, Aya A., Yahia, Abdelrahman, Samir, Omar, Bakry, Usama, Amer, Khaled, ElNaqeeb, Mostafa, Hassan, Wael, Talat, Hala S., Farawela, Hala M., Hamdy, Mona S., Soliman, May S., El Sissy, Maha H., Ezzelarab, Moushira H., El khateeb, Sara M., Soliman, Lamyaa H., Haddad, Sara E., Hatem, Ashraf, Ismail, Mohamed S., Hossam, Maha, Mansour, Tarek, Shalaby, Lobna, Soliman, Sonia, Hassan, Reem, Hammad, Mahmoud, Abdo, Ibrahim, Magdeldin, Sameh, ElHaddad, Alaa, Abouelnaga, Sherif, and Sayed, Ahmed A.

Published
2022
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18. Effectiveness of virtual teaching of diagnostic and interventional imaging fundamentals to Egyptian medical students: an analytical cross-sectional study

Author

Negm, Ahmed S., Elhatw, Ahmed, Badawy, Mohamed, Gioe, Meredith L., Khan, Sana, Hammad, Mahmoud F., Shalaby, Nada, Choucair, Ferial, Saad, Mariam Ahmed, Elfeel, Amany, Elbatal, Mariam, Saenz, Florentino, Shehata, Mostafa Ahmed, Patel, Parth, Aly, Muhammad, Khalifa, Islam, Kamel, Serageldin, ElHefnawi, Yara, Fahmy, Mohamed Ismael, Rohren, Scott, Hussein, Mohamed Yasser, Elsaiey, Ahmed, Zitoun, Owiss, and Elsayes, Khaled M.

Published
2022
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19. Teaching radiology in Egyptian medical schools: Where do we stand and how can we start?

Author

Badawy, Mohamed, Rohren, Scott, Elhatw, Ahmed, Negm, Ahmed S., Ahmed, Amr, Khalifa, Islam, Shehata, Mostafa Ahmed, ElHefnawi, Yara, Saenz, Florentino, Kamel, Serageldin, Saad, Mariam Ahmed, Fahmy, Mohamed Ismael, Ghannam, Sammar, Abusaif, Abdelrahman, Hussein, Mohamed Yasser, Elbatal, Mariam, Shalaby, Nada, Hammad, Mahmoud F., Elfeel, Amany, Choucair, Ferial, Patel, Parth, and Elsayes, Khaled M.

Published
2022
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20. Iraq in the American strategy during World War II 1939-1945 AD

Author

Fawaz Hammad Mahmoud

Subjects
iraq, america, world war ii, History of scholarship and learning. The humanities, AZ20-999
Abstract

The research aims to highlight the position of Iraq in the American strategy during the Second World War (1939-1945) and the areas and aspects through which the United States of America sought to enter Iraq, taking advantage of the war and economic lost conditions that Iraq was going through, and the outbreak of the May 1941 uprising in it, and the need for its location The geopolitical importance in the war against the Axis powers that tried to strengthen their relations with the nationalist trend represented by Rashid Ali Al-Kilani and the Four Colonels and the role of the United States of America in supporting Britain, to abort the May 1941 uprising, and the return of the British to occupy Iraq again, and turn it into an arena for international conflict during World War II and exploitation The United States of America to establish its interests in this country, which enjoys economic capabilities and a strategic location for the richest of a great power such as the United States of America seeks to control the Middle East region, leaving it to others

Published
2021
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21. A Taxonomy of Social Engineering Defense Mechanisms

Author

Alharthi, Dalal N., Hammad, Mahmoud M., Regan, Amelia C., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Arai, Kohei, editor, Kapoor, Supriya, editor, and Bhatia, Rahul, editor

Published
2020
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22. Enhanced COVID-19 Detection from X-ray Images with Convolutional Neural Network and Transfer Learning.

Author

Bani Baker, Qanita, Hammad, Mahmoud, Al-Smadi, Mohammed, Al-Jarrah, Heba, Al-Hamouri, Rahaf, and Al-Zboon, Sa'ad A.

Subjects
CONVOLUTIONAL neural networks, ARTIFICIAL neural networks, COVID-19 pandemic, DEEP learning, X-ray imaging
Abstract

The global spread of Coronavirus (COVID-19) has prompted imperative research into scalable and effective detection methods to curb its outbreak. The early diagnosis of COVID-19 patients has emerged as a pivotal strategy in mitigating the spread of the disease. Automated COVID-19 detection using Chest X-ray (CXR) imaging has significant potential for facilitating large-scale screening and epidemic control efforts. This paper introduces a novel approach that employs state-of-the-art Convolutional Neural Network models (CNNs) for accurate COVID-19 detection. The employed datasets each comprised 15,000 X-ray images. We addressed both binary (Normal vs. Abnormal) and multi-class (Normal, COVID-19, Pneumonia) classification tasks. Comprehensive evaluations were performed by utilizing six distinct CNN-based models (Xception, Inception-V3, ResNet50, VGG19, DenseNet201, and InceptionResNet-V2) for both tasks. As a result, the Xception model demonstrated exceptional performance, achieving 98.13% accuracy, 98.14% precision, 97.65% recall, and a 97.89% F1-score in binary classification, while in multi-classification it yielded 87.73% accuracy, 90.20% precision, 87.73% recall, and an 87.49% F1-score. Moreover, the other utilized models, such as ResNet50, demonstrated competitive performance compared with many recent works. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Impacts of Covid-19 on Developing Countries: A Comparative Study on Foreign Trade Between China and Egypt

Author

Hammad, Mahmoud A., Elhusseiny, Hussein Magdy, Hammad, Dina Adel, and Obrecht, Matevz

Subjects
Epidemics -- Asia -- Africa -- China -- Egypt, Exports -- Comparative analysis, Ports -- Comparative analysis -- International trade, Shipping industry -- International trade -- Comparative analysis, Developing countries -- Comparative analysis, Business, World Health Organization
Abstract

Purpose: Foreign trade faces occasionally many changes and challenges. The latest of these challenges is the Covid-19 pandemic, which has negatively affected the flow of goods. Covid-19's led to a slowdown in global trade affecting imports and exports of commodities. Foreign trade is mainly tied to the maritime transport as approximately 80% of goods are seaborne. Besides, China is considered as home to seven of the world's 10 busiest ports. Moreover, Egypt is a major player in international trade due to its position and location as it connects the three continents Africa, Europe, and Asia through Suez-canal, Red and Mediterranean Sea. Thus, the purpose of this research is to study the impact of Covid-19 on foreign trade goods statistics through conducting a comparative study of the effects on Egypt and China. Design/methodology/approach: The study combined the qualitative and quantitative approaches. The quantitative data were collected using a survey whereas the qualitative aspects were done through conducting interviews and analyzing the literature. Findings: This study has found that effect of Covid-19 on cargo traffic in the Chinese and Egyptian markets has led to a significant decline in imports and exports growth rate. Research limitations: This study has found some limitations related to studying the effect of Covid-19 on inland transport of cargo in both countries. Originality: The value of this cross-national research is to highlight the impact of the Covid-19 pandemic on the imported and exported goods using a comparative approach between China and Egypt. Keywords: Foreign trade, Covid-19, Maritime, Air, Egypt, China Category: Applied Paper, 1. Introduction The foreign trade goes through different stages, some of which are characterized by expansion and increase of growth rates or other stages that may have some of contractions [...]

Published
2021

29. Methods and Models for Electric Load Forecasting: A Comprehensive Review

Author

Hammad Mahmoud A., Jereb Borut, Rosi Bojan, and Dragan Dejan

Subjects
electric load forecasting, modeling electricity loads, methods and models of forecasting, Transportation engineering, TA1001-1280
Abstract

Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.

Published
2020
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31. COVID-19 Management and Outcome of 76 Pediatric Cancer Patients: A Single Centre Experience from a Developing Country

Author

Hammad, Mahmoud, primary, shalaby, lobna, additional, Sidhom, Iman, additional, Sherif, Nancy, additional, Abdo, Ibrahim, additional, Soliman, Sonya, additional, Madney, Youssef, additional, Hassan, Reem, additional, Elmeniawy, Shaimaa, additional, Khamis, Nagwa, additional, zaki, Iman, additional, Mansour, Tarek, additional, El-Ansary, Mohamed, additional, El-Halfawy, Ahmed, additional, Abouelnaga, Sherif, additional, and Elhaddad, Alaa, additional

Published
2024
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32. Multidisciplinary approach of teaching radiology to medical students in Egypt: Is this an effective method?

Author

Nabhani, Yasmeen, Xie, Victoria K., Badawy, Mohamed, Karim, Rehan, Abdullatif, Umayma, Negm, Ahmed S., Bhosale, Hrishabh, Rohren, Scott, Elhatw, Ahmed, Ghannam, Sammar, Abusaif, Abdelrahman, Elsamaloty, Mazzin, Shalaby, Nada, Choucair, Ferial, Khalifa, Islam, Saad, Mariam Ahmed, Patel, Parth, Almubaid, Zaid, Shehata, Mostafa Ahmed, ElHefnawi, Yara, Kamal, Serageldin, Hammad, Mahmoud F., and Elsayes, Khaled M.

Published
2021
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37. Using Deep Learning Techniques to Detect Hate and Abusive Language in Arabic Tweets.

Author

Al-Jarrah, Heba, Al-Smadi, Mohammad, Hammad, Mahmoud, and Shannaq, Fatima

Subjects
LANGUAGE models, INVECTIVE, DEEP learning, DIGITAL communications, HATE speech, SOCIAL media
Abstract

Billions of people spend hours on social media platforms every day. While there are numerous known benefits of social media, hate speech and abusive language on social media platforms have become an increasingly serious social problem affecting individuals and societies' psychological state. Detecting and preventing hate speech and abusive language is a crucial task for healthy and safety digital communication. To overcome this important social problem, we propose four various deep learning and pre-trained models: (i) Ensemble deep learning model, (ii) Multilingual BERT model, (iii) Arabic BERT model, and (iv) ALBERT model to detect hate speech and abusive language in Arabic text. To that end, we utilized the L-HSAB Arabic dataset to build our models, and we utilized the OSACT dataset to evaluate the generalizability of our model's architecture. Our model tackles two classification tasks: a binary classification and a multiclass classification task. Our Arabic Bidirectional Encoder Representations from Transformers (BERT)-based model achieved the best performance on the binary classification task with an F1-score of 90.8%. While our Multilingual BET-based model obtained the best result on the multi-class classification task with an F1-score of 80.0%. Finally, the generalizability experiment of our best-performing mod-el on the binary classification task achieved an F1-score of 90.2% on the OSACT dataset. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Pediatric ependymoma: A single-center experience from a developing country

Author

Hammad, Mahmoud, Hosny, Maryhan, Khalil, Ehab, Alfaar, Ahmad, and Fawzy, Mohamed

Subjects
United States. National Cancer Institute, Development and progression, Vincristine, Carboplatin, Radiotherapy, Pediatrics, Developing countries, Brain tumors -- Development and progression
Published
2021

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