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@article{176872,
        author = {PAILA MADHURI and VOONNA SAI GAYATHRI and RUNKANA ADITYA PAVAN KUMAR and VANA KAVYASRI},
        title = {Analyzing Adverse Reactions In Oncology Using Various Drug Patterns},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {6695-6699},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176872},
        abstract = {Chemotherapy is a treatment for cancer that uses strong medicines to kill cancer cells. However, these medicines can also affect healthy cells, which can lead to side effects. Common side effects include feeling very tired (fatigue), nausea, vomiting, and hair loss.
This project is on developing a Machine Learning model for Predicting the Adverse drug reactions in chemotherapy patients. Predicting the adverse drug reactions can considerably reduce the impact on the oncology in cancer patients who are mostly subjected to aggressive and highly toxic treatment regiments. This project is intended to use models to predict these side effects before they occur. Through studying patient information and drug details, we can train the model to recognize patterns. This will help us to identify ADRs early. We used openly available adverse drug event data, preprocess the data, feature extraction, and explore various Machine learning models to assess their performance in predicting adverse effects by applying different Machine learning models like K-NN(Nearest Neighbors),SVM (support vector machine),Logistic Regression and Random Forest. Different Metrics like Accuracy, AUC, F1 Score, Precision, Recall. Among all these the Radom Forest performs well with Accuracy of 0.98 and Metrics of SVM are Accuracy: 0.88, Precision: 0.94, Recall: 0.93, F1 Score: 0.93, AUC: 0.71. This Study shows that This study highlights the potential of machine learning in predicting adverse drug reactions, which can improve patient care and minimize the negative effects of chemotherapy.},
        keywords = {Adverse drug reactions, Machine learning, Chemotherapy, oncology.},
        month = {April},
        }