• Raksha
• Krishna C
• Muhammed Mikdad U M
• Fatheen Yusuf
• Dr. Jithendra PR Nayak, Shreya Shetty, Suresha D

The system tackles the problem of diabetes risk assessment in individuals by predicting “Diabetes Prediction Using Medical Reports” with the help of their detailed medical records from health institutions and applying logics and rules-based machine learning techniques on. The advanced system aims to analyze key key health metrics and potential risk factors including glucose concentration, body mass index (BMI), age, blood pressure, insulin concentration, family medicalhistory, and several other variables. By analyzing these factors, the system can develop a model and enabling proactive steps at an early stage. The flow of work in a project begins with feature selection highlighting the most influential factors. Then data normalization adjusting the scale of the features to a standard range and removing the missing entries that make the model unusable, known as data cleansing, is done. Logistic Regression works best for problems such as this with a clear delineation, and within a well-balanced dataset. Moreover, the dataset should best represent the entire population of patients in terms of age, sex, and other distinguishing features as this intends to improve prediction accuracy. The overall effectiveness is analyzed with additional advanced measures for model evaluation accuracy, precision, recall, F-score, especially in their collective form give a better image as the provide proper evaluation.

Diabetes prediction, Medical Reports, Machine Learning, Feature Selection, Data Normalisation,Data Cleansing, Risk Assessment, Health Indicator

"DIABETES PREDICTION USING MEDICAL REPORT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.28-35, July-2025, Available :http://www.jetir.org/papers/JETIRGX06006.pdf

"DIABETES PREDICTION USING MEDICAL REPORT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp28-35, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06006.pdf