No.

Publication Date

Citing Article

1

2025

Nojoud Noureldayim Elsayid, Elwaleed Idrees Aydaross Adam, Samah Mohamed Yousif Mahmoud, Hoyam Saadeldeen, Muhammad Nauman, Tayseir Ahmed Ali Ahmed, Belgees Altigani Hamza Yousif, Allaa Ibrahim Awad Taha. The Role of Machine Learning Approaches in Pediatric Oncology: A Systematic Review, Cureus. 2025;   https://doi.org/10.7759/cureus.77524

2

2024

Nour Mohamed, Tamer Rabie. Digital Imaging and Artificial Intelligence in Infantile Hemangioma: A Systematic Literature Review, Biomimetics. 2024; 9: 663.  https://doi.org/10.3390/biomimetics9110663

3

2024

Jianbo Shao, Yi Lu, Zhihan Yan, Xin Li. 2024; 203.  https://doi.org/10.1007/978-981-99-8441-1_14

4

2024

Amparo López-Carrasco, Karina Parra-Haro, Isaac Vieco-Martí, Sofía Granados-Aparici, Juan Díaz-Martín, Carmen Salguero-Aranda, Delia Acevedo-León, Enrique de Álava, Samuel Navarro, Rosa Noguera. Characterization of Vitronectin Effect in 3D Ewing Sarcoma Models: A Digital Microscopic Analysis of Two Cell Lines, Cancers. 2024; 16: 3347.  https://doi.org/10.3390/cancers16193347

5

2024

Fu-Sheng Chou, Neil Rowen, Joyce Javier, Ashwini Lakshmanan. Predicting childhood outcomes through standardizing disease definitions and promoting multicenter enrollment, Pediatric Research. 2024; 96: 1103.  https://doi.org/10.1038/s41390-024-03489-6

6

2025

Ekta Tiwari, Siddharth Gupta, Anudeep Pavulla, Mustafa Al-Maini, Rajesh Singh, Esma R. Isenovic, Sumit Chaudhary, John L. Laird, Laura Mantella, Amer M. Johri, Luca Saba, Jasjit S. Suri. Artificial intelligence-based multiclass diabetes risk stratification for big data embedded with explainability: From machine learning to attention models, Biomedical Signal Processing and Control. 2025; 106: 107672107672.  https://doi.org/10.1016/j.bspc.2025.107672

7

2024

Shuping Wen, Stefan Theobald, Pilar Gangas, Karina C. Borja Jiménez, Johannes H.M. Merks, Reineke A. Schoot, Marcel Meyerheim, Norbert Graf. A practical guide to apply AI in childhood cancer: Data collection and AI model implementation, EJC Paediatric Oncology. 2024; 4: 100197100197.  https://doi.org/10.1016/j.ejcped.2024.100197

8

2025

Archana Reddy Bongurala, Dhaval Save, Ankit Virmani. Progressive role of artificial intelligence in treatment decision-making in the field of medical oncology, Frontiers in Medicine. 2025; 12: 1533910.  https://doi.org/10.3389/fmed.2025.1533910

9

2025

Elham Shafighi Shahri, Akram Ehsasatvatan, Mohammad Salavatizadeh, Somayeh Talaeepur. Artificial Intelligence Applications in Pediatric Oncology Imaging: A Systematic Review of Diagnostic, Prognostic, and Therapeutic Evaluation Tools, InfoScience Trends. 2025; 2: 36.  https://doi.org/10.61186/ist.202502.03.04

10

2024

Kirk D. Wyatt, Natasha Alexander, Gerard D. Hills, Wayne H. Liang, Stephan Kadauke, Samuel L. Volchenboum, Amir Mian, Charles A. Phillips. Making sense of artificial intelligence and large language models—including ChatGPT—in pediatric hematology/oncology, Pediatric Blood & Cancer. 2024; 71: e31143.  https://doi.org/10.1002/pbc.31143