AI/ML in Preventive Healthcare: Building Multi-Disease Prediction Systems for Early Interventions
Sonam Juneja, Gursimran Kaur, Purnima Bakshi, Bhoopesh Singh Bhati · 2025
In today's healthcare, it has become crucial to predict multiple diseases such as PCOD, breast cancer and cervical cancer that have become more important to improve patient care. The proposed system is to be used by healthcare professionals to predict multiple disease with given input datasets. The stated system learns using machine learning capabilities including XGboost and CatBoost, in an effort to predict the presence of these cancers by identifying parameters that suggest the existence of the cancer. The proposed study shows that XGboost performs better than CATBoost in terms of Accuracy with 95 percent, making it suitable for integration with existing health care systems and enabling real time predictions to give doctors more powerful tools for diagnosing and developing personalized treatment plans for cancer patients.