• Patnana Koteswara Rao
• Chappa Divya
• Nalukurthi Abhinav
• Gosangi Jeevankumar
• P Yugandhar Reddy

Since World War II (1939–1945), the use of synthetic fertilizers and pesticides, collectively known as agrochemicals, has grown significantly to avoid pests, reduce agricultural losses, and enhance food quality and yields. However, exposure to these agrochemicals poses substantial health risks to farmers and chemical workers. Researchers found that this exposure may be linked to many serious health issues including Cancers, Neurological disorders, skin problems, respiratory diseases, etc. Despite the critical importance of addressing these health risks due to the lack of awareness and symptoms being unreported , diagnosing diseases caused by agrochemical exposure remains . Overcoming these challenges requires a multi-faceted approach. Our research project focuses on early diagnosis of diseases through intelligent diagnostic tools based on specific symptoms. Early detection can enable timely medical attention, potentially preventing serious health complications.By leveraging the power of AI and ML, our study performs two main tasks: multiclass classification on numerical data using the XGBoost classifier and binary image classification using a CNN Sequential_5 model. The XGBoost classifier has proven to be highly effective for multiclass classification tasks on numerical data, achieving near-perfect accuracy and consistency. The CNN model demonstrates high reliability and generalization capability in binary image classification, effectively distinguishing between the two main diseases caused by exposure namely Contact Dermatitis and Skin Cancer. The successful use of these diagnostic models has far-reaching implications in healthcare, policy-making in chemical and agricultural workplaces. This research also helps in promoting the preventive measures and creating the awareness among people about the adverse effects of using agrochemicals.

Agrochemical Toxicity, Occupational Exposure, Skin Cancers, Contact Dermatitis, Respiratory Problems, Disease Diagnosis, Predictive Models, Preventive Measures, Improving Awareness.

"Intelligent Diagnosis of Adverse Agrochemical Effects on Chemical & Farm Workers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h391-h403, June-2024, Available :http://www.jetir.org/papers/JETIR2406745.pdf

"Intelligent Diagnosis of Adverse Agrochemical Effects on Chemical & Farm Workers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph391-h403, June-2024, Available at : http://www.jetir.org/papers/JETIR2406745.pdf