Aasim, M. Et Al. 2023. Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.. Environmental Science and Pollution Research , vol.30, no.14 , 40206-40217.

Aasim, M., Ali, S. A., Aydin, S., Bakhsh, A., Sogukpinar, C., Karatas, M., ... Khawar, K. M.(2023). Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.. Environmental Science and Pollution Research , vol.30, no.14, 40206-40217.

Aasim, Muhammad Et Al. "Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.," Environmental Science and Pollution Research , vol.30, no.14, 40206-40217, 2023

Aasim, Muhammad Et Al. "Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.." Environmental Science and Pollution Research , vol.30, no.14, pp.40206-40217, 2023

Aasim, M. Et Al. (2023) . "Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.." Environmental Science and Pollution Research , vol.30, no.14, pp.40206-40217.

@article{article, author={Muhammad Aasim Et Al. }, title={Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.}, journal={Environmental Science and Pollution Research}, year=2023, pages={40206-40217} }