Open Access
| Issue |
E3S Web Conf.
Volume 650, 2025
The 10th International Conference on Energy, Environment, and Information Systems (ICENIS 2025)
|
|
|---|---|---|
| Article Number | 02035 | |
| Number of page(s) | 9 | |
| Section | Environment | |
| DOI | https://doi.org/10.1051/e3sconf/202565002035 | |
| Published online | 10 October 2025 | |
- Janik-Karpinska E, Brancaleoni R, Niemcewicz M, Wojtas W, Foco M, Podogrocki M, et al. Healthcare Waste-A Serious Problem for Global Health. Healthcare (Basel, Switzerland). 2023;11(2): 242. https://doi.org/10.3390/healthcare11020242. [Google Scholar]
- Thakur V, Mangla SK, Tiwari B. Managing healthcare waste for sustainable environmental development: A hybrid decision approach. Business Strategy and the Environment. 2021 Jan;30(1):357-73. [Google Scholar]
- Zhang HJ, Zhang YH, Wang Y, Yang YH, Zhang J, Wang YL, Wang JL. Investigation of medical waste management in Gansu Province, China. Waste Management & Research. 2013 Jun;31(6):655-9. [Google Scholar]
- Padmanabhan, K.K.; Barik, D. Health Hazards of Medical Waste and Its Disposal. In Energy from Toxic Organic Waste for Heat and Power Generation; Elsevier: Amsterdam, The Netherlands, 2019; pp. 99–118 [Google Scholar]
- Yazie, T.D.; Tebeje, M.G.; Chufa, K.A. Healthcare Waste Management Current Status and Potential Challenges in Ethiopia: A Systematic Review. BMC Res. Notes 2019, 12, 285 [Google Scholar]
- Soni U, Roy A, Verma A, Jain V. Forecasting municipal solid waste generation using artificial intelligence models—a case study in India. SN Applied Sciences. 2019 Feb;1(2):162. [Google Scholar]
- Wang K, Zhao Y, Gangadhari RK, Li Z. Analyzing the adoption challenges of the Internet of things (Iot) and artificial intelligence (ai) for smart cities in china. Sustainability. 2021 Oct 3;13(19):10983. [Google Scholar]
- Carrazco, Diego Cajamarca, Tobar-Ruiz, María Gabriela, López, Diego Marcelo Almeida, Hermida, Carlos Eduardo Cevallos, Arellano, Verónica Magdalena Llangari,Tobar, Mateo Augusto Zavala;Godoy, María Magdalena Paredes.Bibliometric analysis of the applicability of artificial intelligence in the integrated management of medical waste. Hybrid Gold Open Access.Volume 31 January 2024. [Google Scholar]
- Fang B, Yu J, Chen Z, Osman AI, Farghali M, Ihara I, Hamza EH, Rooney DW, Yap PS. Artificial intelligence for waste management in smart cities: a review. Environmental Chemistry Letters. 2023 Aug;21(4):1959-89. [CrossRef] [Google Scholar]
- Bamakan SM, Malekinejad P, Ziaeian M. Towards blockchain-based hospital waste management systems; applications and future trends. Journal of Cleaner Production. 2022 May 15;349:131440. [Google Scholar]
- Dewasiri NJ, Rathnasiri MS, Karunarathna KS. Artificial Intelligence-Driven Technologies for Environmental Sustainability in the Healthcare Industry. In Transforming Healthcare Sector Through Artificial Intelligence and Environmental Sustainability 2025 Jan 23 (pp. 67-87). Singapore: Springer Nature Singapore. [Google Scholar]
- Sharma V, Jamwal A, Agrawal R, Pratap S. A review on digital transformation in healthcare waste management: Applications, research trends and implications. Waste Management & Research. 2025 Jun;43(6):828-49. [Google Scholar]
- Chenniappan T, Devarajan Y. A critical analysis of the role of artificial intelligence and machine learning in enhancing nuclear waste management. Kerntechnik. 2024 Oct 28;89(5):586-94. [Google Scholar]
- Selvam DC, Devarajan Y, Raja T. Exploring the potential of artificial intelligence in nuclear waste management: Applications, challenges, and future directions. Nuclear Engineering and Design. 2025 Jan 1;431:113719. [Google Scholar]
- Sorkhi A, Pourasghar F. Artificial intelligence application in healthcare management: a review of challenges. International Journal of Healthcare Technology and Management. 2024;21(1):79-88. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.