@article {49423, title = {Explainable AI-assisted web application in cancer drug value prediction}, journal = {MethodsX}, volume = {12}, year = {2024}, month = {JUN}, type = {Article}, abstract = {
In recent years, there has been an increase in the interest in adopting Explainable Artificial Intelligence (XAI) for healthcare. The proposed system includes
While the model is evaluated on Lung Cancer data, the architecture offered in the proposed solution is cancer agnostic. It may be scaled out to other cancer cell data if the properties are similar. The work presents a viable route for customizing treatments and improving patient outcomes in oncology by combining XAI with a large dataset. This research attempts to create a framework where a user can upload a test case and receive forecasts with explanations, all in a portable PDF report.
}, author = {Kothari, Sonali and Sharma, Shivanandana and Shejwal, Sanskruti and Kazi, Aqsa and D{\textquoteright}Silva, Michela and Karthikeyan, M.} }