Shoaib Hassan

Decoding fish health trajectories across anthropogenically impacted habitats: integrating machine learning approaches for ecological assessment in Pakistan

The findings support the Random Forest approach as a high-precision machine learning technique for aquatic watershed risk-indexing and multi-tier biomonitoring and could be valuable for fish researchers, scientists, technicians, and farm operators seeking to improve learning and adaptation to new technologies.